3. PMAPI–The Performance Metrics API¶
This chapter describes the Performance Metrics Application Programming Interface (PMAPI) provided with Performance Co-Pilot (PCP).
The PMAPI is a set of functions and data structure definitions that allow client applications to access performance data from one or more Performance Metrics Collection Daemons (PMCDs) or from PCP archive logs. The PCP utilities are all written using the PMAPI.
The most common use of PCP includes running performance monitoring utilities on a workstation (the monitoring system) while performance data is retrieved from one or more remote collector systems by a number of PCP processes. These processes execute on both the monitoring system and the collector systems. The collector systems are typically servers, and are the targets for the performance investigations.
In the development of the PMAPI the most important question has been, “How easily and quickly will this API enable the user to build new performance tools, or exploit existing tools for newly available performance metrics?” The PMAPI and the standard tools that use the PMAPI have enjoyed a symbiotic evolution throughout the development of PCP.
It will be convenient to differentiate between code that uses the PMAPI and code that implements the services of the PMAPI. The former will be termed “above the PMAPI” and the latter “below the PMAPI.”
3.1. Naming and Identifying Performance Metrics¶
Across all of the supported performance metric domains, there are a large number of performance metrics. Each metric has its own description, format, and semantics. PCP presents a uniform interface to these metrics above the PMAPI, independent of the source of the underlying metric data. For example, the performance metric hinv.physmem has a single 32-bit unsigned integer value, representing the number of megabytes of physical memory in the system, while the performance metric disk.dev.total has one 32-bit unsigned integer value per disk spindle, representing the cumulative count of I/O operations involving each associated disk spindle. These concepts are described in greater detail in Section 2.3, “Domains, Metrics, Instances and Labels”.
For brevity and efficiency, internally PCP avoids using names for performance metrics, and instead uses an identification scheme that unambiguously associates a single integer with each known performance metric. This integer is known as a Performance Metric Identifier, or PMID. For functions using the PMAPI, a PMID is defined and manipulated with the typedef pmID.
Below the PMAPI, the integer value of the PMID has an internal structure that reflects the details of the PMCD and PMDA architecture, as described in Section 2.3.3, “Metrics”.
Above the PMAPI, a Performance Metrics Name Space (PMNS) is used to provide a hierarchic classification of external metric names, and a one-to-one mapping of external names to internal PMIDs. A more detailed description of the PMNS can be found in the Performance Co-Pilot User’s and Administrator’s Guide.
The default PMNS comes from the performance metrics source, either a PMCD process or a PCP archive. This PMNS always reflects the available metrics from the performance metrics source.
3.2. Performance Metric Instances¶
When performance metric values are returned across the PMAPI to a requesting application, there may be more than one value for a particular metric; for example, independent counts for each CPU, or each process, or each disk, or each system call type, and so on. This multiplicity of values is not enumerated in the Name Space, but rather when performance metrics are delivered across the PMAPI.
The notion of metric instances is really a number of related concepts, as follows:
A particular performance metric may have a set of associated values or instances.
The instances are differentiated by an instance identifier.
An instance identifier has an internal encoding (an integer value) and an external encoding (a corresponding external name or label).
The set of all possible instance identifiers associated with a performance metric on a particular host constitutes an instance domain.
Several performance metrics may share the same instance domain.
Consider Example 3.1. Metrics Sharing the Same Instance Domain:
Example 3.1. Metrics Sharing the Same Instance Domain
$ pminfo -f filesys.free
filesys.free
inst [1 or “/dev/disk0”] value 1803
inst [2 or “/dev/disk1”] value 22140
inst [3 or “/dev/disk2”] value 157938
The metric filesys.free has three values, currently 1803, 22140, and 157938. These values are respectively associated with the instances identified by the internal identifiers 1, 2 and 3, and the external identifiers /dev/disk0, /dev/disk1, and /dev/disk2. These instances form an instance domain that is shared by the performance metrics filesys.capacity, filesys.used, filesys.free, filesys.mountdir, and so on.
Each performance metric is associated with an instance domain, while each instance domain may be associated with many performance metrics. Each instance domain is identified by a unique value, as defined by the following typedef declaration:
typedef unsigned long pmInDom;
The special instance domain PM_INDOM_NULL is reserved to indicate that the metric has a single value (a singular instance domain). For example, the performance metric mem.freemem always has exactly one value. Note that this is semantically different to a performance metric like kernel.percpu.cpu.sys that has a non-singular instance domain, but may have only one value available; for example, on a system with a single processor.
In the results returned above the PMAPI, each individual instance within an instance domain is identified by an internal integer instance identifier. The special instance identifier PM_IN_NULL is reserved for the single value in a singular instance domain. Performance metric values are delivered across the PMAPI as a set of instance identifier and value pairs.
The instance domain of a metric may change with time. For example, a machine may be shut down, have several disks added, and be rebooted. All performance metrics associated with the instance domain of disk devices would contain additional values after the reboot. The difficult issue of transient performance metrics means that repeated requests for the same PMID may return different numbers of values, or some changes in the particular instance identifiers returned. This means applications need to be aware that metric instantiation is guaranteed to be valid only at the time of collection.
Note
Some instance domains are more dynamic than others. For example, consider the instance domains behind the performance metrics proc.memory.rss (one instance per process), swap.free (one instance per swap partition) and kernel.percpu.cpu.intr (one instance per CPU).
3.3. Current PMAPI Context¶
When performance metrics are retrieved across the PMAPI, they are delivered in the context of a particular source of metrics, a point in time, and a profile of desired instances. This means that the application making the request has already negotiated across the PMAPI to establish the context in which the request should be executed.
A metric’s source may be the current performance data from a particular host (a live or real-time source), or a set of archive logs of performance data collected by pmlogger at some remote host or earlier time (a retrospective or archive source). The metric’s source is specified when the PMAPI context is created by calling the pmNewContext function. This function returns an opaque handle which can be used to identify the context.
The collection time for a performance metric is always the current time of day for a real-time source, or current position for an archive source. For archives, the collection time may be set to an arbitrary time within the bounds of the set of archive logs by calling the pmSetMode function.
The last component of a PMAPI context is an instance profile that may be used to control which particular instances from an instance domain should be retrieved. When a new PMAPI context is created, the initial state expresses an interest in all possible instances, to be collected at the current time. The instance profile can be manipulated using the pmAddProfile and pmDelProfile functions.
The current context can be changed by passing a context handle to pmUseContext. If a live context connection fails, the pmReconnectContext function can be used to attempt to reconnect it.
3.4. Performance Metric Descriptions¶
For each defined performance metric, there exists metadata describing it.
A performance metric description (pmDesc structure) that describes the format and semantics of the performance metric.
Help text associated with the metric and any associated instance domain.
Performance metric labels (name:value pairs in pmLabelSet structures) associated with the metric and any associated instances.
The pmDesc structure, in Example 3.2. pmDesc Structure, provides all of the information required to interpret and manipulate a performance metric through the PMAPI. It has the following declaration:
Example 3.2. pmDesc Structure
/* Performance Metric Descriptor */
typedef struct {
pmID pmid; /* unique identifier */
int type; /* base data type (see below) */
pmInDom indom; /* instance domain */
int sem; /* semantics of value (see below) */
pmUnits units; /* dimension and units (see below) */
} pmDesc;
The type field in the pmDesc structure describes various encodings of a metric’s value. Its value will be one of the following constants:
/* pmDesc.type - data type of metric values */
#define PM_TYPE_NOSUPPORT -1 /* not in this version */
#define PM_TYPE_32 0 /* 32-bit signed integer */
#define PM_TYPE_U32 1 /* 32-bit unsigned integer */
#define PM_TYPE_64 2 /* 64-bit signed integer */
#define PM_TYPE_U64 3 /* 64-bit unsigned integer */
#define PM_TYPE_FLOAT 4 /* 32-bit floating point */
#define PM_TYPE_DOUBLE 5 /* 64-bit floating point */
#define PM_TYPE_STRING 6 /* array of char */
#define PM_TYPE_AGGREGATE 7 /* arbitrary binary data */
#define PM_TYPE_AGGREGATE_STATIC 8 /* static pointer to aggregate */
#define PM_TYPE_EVENT 9 /* packed pmEventArray */
#define PM_TYPE_UNKNOWN 255 /* used in pmValueBlock not pmDesc */
By convention PM_TYPE_STRING is interpreted as a classic C-style null byte terminated string.
Event records are encoded as a packed array of strongly-typed, well-defined records within a pmResult structure, using a container metric with a value of type PM_TYPE_EVENT.
If the value of a performance metric is of type PM_TYPE_STRING, PM_TYPE_AGGREGATE, PM_TYPE_AGGREGATE_STATIC, or PM_TYPE_EVENT, the interpretation of that value is unknown to many PCP components. In the case of the aggregate types, the application using the value and the Performance Metrics Domain Agent (PMDA) providing the value must have some common understanding about how the value is structured and interpreted. Strings can be manipulated using the standard C libraries. Event records contain timestamps, event flags and event parameters, and the PMAPI provides support for unpacking an event record - see the pmUnpackEventRecords(3) man page for details. Further discussion on event metrics and event records can be found in Section 3.6, “Performance Event Metrics”.
PM_TYPE_NOSUPPORT indicates that the PCP collection framework knows about the metric, but the corresponding service or application is either not configured or is at a revision level that does not provide support for this performance metric.
The semantics of the performance metric is described by the sem field of a pmDesc structure and uses the following constants:
/* pmDesc.sem - semantics of metric values */
#define PM_SEM_COUNTER 1 /* cumulative count, monotonic increasing */
#define PM_SEM_INSTANT 3 /* instantaneous value continuous domain */
#define PM_SEM_DISCRETE 4 /* instantaneous value discrete domain */
Each value for a performance metric is assumed to be drawn from a set of values that can be described in terms of their dimensionality and scale by a compact encoding, as follows:
The dimensionality is defined by a power, or index, in each of three orthogonal dimensions: Space, Time, and Count (dimensionless). For example, I/O throughput is Space1.Time-1, while the running total of system calls is Count1, memory allocation is Space1, and average service time per event is Time1.Count-1.
In each dimension, a number of common scale values are defined that may be used to better encode ranges that might otherwise exhaust the precision of a 32-bit value. For example, a metric with dimension Space1.Time-1 may have values encoded using the scale megabytes per second.
This information is encoded in the pmUnits data structure, shown in Example 3.3. pmUnits and pmDesc Structures. It is embedded in the pmDesc structure :
The structures are as follows:
Example 3.3. pmUnits and pmDesc Structures
/*
* Encoding for the units (dimensions and
* scale) for Performance Metric Values
*
* For example, a pmUnits struct of
* { 1, -1, 0, PM_SPACE_MBYTE, PM_TIME_SEC, 0 }
* represents Mbytes/sec, while
* { 0, 1, -1, 0, PM_TIME_HOUR, 6 }
* represents hours/million-events
*/
typedef struct {
int pad:8;
int scaleCount:4; /* one of PM_COUNT_* below */
int scaleTime:4; /* one of PM_TIME_* below */
int scaleSpace:4; /* one of PM_SPACE_* below */
int dimCount:4; /* event dimension */
int dimTime:4; /* time dimension */
int dimSpace:4; /* space dimension
} pmUnits; /* dimensional units and scale of value */
/* pmUnits.scaleSpace */
#define PM_SPACE_BYTE 0 /* bytes */
#define PM_SPACE_KBYTE 1 /* kibibytes (1024) */
#define PM_SPACE_MBYTE 2 /* mebibytes (1024^2) */
#define PM_SPACE_GBYTE 3 /* gibibytes (1024^3) */
#define PM_SPACE_TBYTE 4 /* tebibytes (1024^4) */
#define PM_SPACE_PBYTE 5 /* pebibytes (1024^5) */
#define PM_SPACE_EBYTE 6 /* exbibytes (1024^6) */
#define PM_SPACE_ZBYTE 7 /* zebibytes (1024^7) */
#define PM_SPACE_YBYTE 8 /* yobibytes (1024^8) */
/* pmUnits.scaleTime */
#define PM_TIME_NSEC 0 /* nanoseconds */
#define PM_TIME_USEC 1 /* microseconds */
#define PM_TIME_MSEC 2 /* milliseconds */
#define PM_TIME_SEC 3 /* seconds */
#define PM_TIME_MIN 4 /* minutes */
#define PM_TIME_HOUR 5 /* hours */
/*
* pmUnits.scaleCount (e.g. count events, syscalls,
* interrupts, etc.) -- these are simply powers of 10,
* and not enumerated here.
* e.g. 6 for 10^6, or -3 for 10^-3
*/
#define PM_COUNT_ONE 0 /* 1 */
Metric and instance domain help text are simple ASCII strings. As a result, there are no special data structures associated with them. There are two forms of help text available for each metric and instance domain, however - one-line and long form.
Example 3.4. Help Text Flags
#define PM_TEXT_ONELINE 1
#define PM_TEXT_HELP 2
Labels are stored and communicated within PCP using JSONB formatted strings in the json field of a pmLabelSet structure. This format is a restricted form of JSON suitable for indexing and other operations. In JSONB form, insignificant whitespace is discarded, and order of label names is not preserved. Within the PMCS, however, a lexicographically sorted key space is always maintained. Duplicate label names are not permitted. The label with highest precedence in the label hierarchy (context level labels, domain level labels, and so on) is the only one presented.
Example 3.5. pmLabel and pmLabelSet Structures
typedef struct {
uint name : 16; /* label name offset in JSONB string */
uint namelen : 8; /* length of name excluding the null */
uint flags : 8; /* information about this label */
uint value : 16; /* offset of the label value */
uint valuelen : 16; /* length of value in bytes */
} pmLabel;
/* flags identifying label hierarchy classes. */
#define PM_LABEL_CONTEXT (1<<0)
#define PM_LABEL_DOMAIN (1<<1)
#define PM_LABEL_INDOM (1<<2)
#define PM_LABEL_CLUSTER (1<<3)
#define PM_LABEL_ITEM (1<<4)
#define PM_LABEL_INSTANCES (1<<5)
/* flag identifying extrinsic labels. */
#define PM_LABEL_OPTIONAL (1<<7)
typedef struct {
uint inst; /* PM_IN_NULL or the instance ID */
int nlabels; /* count of labels or error code */
char *json; /* JSONB formatted labels string */
uint jsonlen : 16; /* JSON string length byte count */
uint padding : 16; /* zero, reserved for future use */
pmLabel *labels; /* indexing into the JSON string */
} pmLabelSet;
The pmLabel labels array provides name and value indexes and lengths in the json string.
The flags field is a bitfield identifying the hierarchy level and whether this name:value pair is intrinsic (optional) or extrinsic (part of the mandatory, identifying metadata for the metric or instance). All other fields are offsets and lengths in the JSONB string from an associated pmLabelSet structure.
3.5. Performance Metrics Values¶
An application may fetch (or store) values for a set of performance metrics, each with a set of associated instances, using a single pmFetch (or pmStore) function call. To accommodate this, values are delivered across the PMAPI in the form of a tree data structure, rooted at a pmResult structure. This encoding is illustrated in Figure 3.1. A Structured Result for Performance Metrics from pmFetch, and uses the component data structures in Example 3.6. pmValueBlock and pmValue Structures:
Example 3.6. pmValueBlock and pmValue Structures
typedef struct {
int inst; /* instance identifier */
union {
pmValueBlock *pval; /* pointer to value-block */
int lval; /* integer value insitu */
} value;
} pmValue;
Figure 3.1. A Structured Result for Performance Metrics from pmFetch¶
The internal instance identifier is stored in the inst element. If a value for a particular metric-instance pair is a 32-bit integer (signed or unsigned), then it will be stored in the lval element. If not, the value will be in a pmValueBlock structure, as shown in Example 3.7. pmValueBlock Structure, and will be located via pval:
The pmValueBlock structure is as follows:
Example 3.7. pmValueBlock Structure
typedef struct {
unsigned int vlen : 24; /* bytes for vtype/vlen + vbuf */
unsigned int vtype : 8; /* value type */
char vbuf[1]; /* the value */
} pmValueBlock;
The length of the pmValueBlock (including the vtype and vlen fields) is stored in vlen. Despite the prototype declaration of vbuf, this array really accommodates vlen minus sizeof(vlen) bytes. The vtype field encodes the type of the value in the vbuf[] array, and is one of the PM_TYPE_* macros defined in <pcp/pmapi.h>.
A pmValueSet structure, as shown in Example 3.8. pmValueSet Structure, contains all of the values to be returned from pmFetch for a single performance metric identified by the pmid field.
Example 3.8. pmValueSet Structure
typedef struct {
pmID pmid; /* metric identifier */
int numval; /* number of values */
int valfmt; /* value style, insitu or ptr */
pmValue vlist[1]; /* set of instances/values */
} pmValueSet;
If positive, the numval field identifies the number of value-instance pairs in the vlist array (despite the prototype declaration of size 1). If numval is zero, there are no values available for the associated performance metric and vlist[0] is undefined. A negative value for numval indicates an error condition (see the pmErrStr(3) man page) and vlist[0] is undefined. The valfmt field has the value PM_VAL_INSITU to indicate that the values for the performance metrics should be located directly via the lval member of the value union embedded in the elements of vlist; otherwise, metric values are located indirectly via the pval member of the elements of vlist.
The pmResult structure, as shown in Example 3.9. pmResult Structure, contains a time stamp and an array of numpmid pointers to pmValueSet.
Example 3.9. pmResult Structure
/* Result returned by pmFetch() */
typedef struct {
struct timeval timestamp; /* stamped by collector */
int numpmid; /* number of PMIDs */
pmValueSet *vset[1]; /* set of value sets */
} pmResult
There is one pmValueSet pointer per PMID, with a one-to-one correspondence to the set of requested PMIDs passed to pmFetch.
Along with the metric values, the PMAPI returns a time stamp with each pmResult that serves to identify when the performance metric values were collected. The time is in the format returned by gettimeofday and is typically very close to the time when the metric values were extracted from their respective domains.
Note
There is a question of exactly when individual metrics may have been collected, especially given their origin in potentially different performance metric domains, and variability in metric updating frequency by individual PMDAs. PCP uses a pragmatic approach, in which the PMAPI implementation returns all metrics with values accurate as of the time stamp, to the maximum degree possible, and PMCD demands that all PMDAs deliver values within a small realtime window. The resulting inaccuracy is small, and the additional burden of accurate individual timestamping for each returned metric value is neither warranted nor practical (from an implementation viewpoint).
The PMAPI provides functions to extract, rescale, and print values from the above structures; refer to Section 3.8.11, “PMAPI Ancillary Support Services”.
3.6. Performance Event Metrics¶
In addition to performance metric values which are sampled by monitor tools, PCP supports the notion of performance event metrics which occur independently to any sampling frequency. These event metrics (PM_TYPE_EVENT) are delivered using a novel approach which allows both sampled and event trace data to be delivered via the same live wire protocol, the same on-disk archive format, and fundamentally using the same PMAPI services. In other words, a monitor tool may be sample and trace, simultaneously, using the PMAPI services discussed here.
Event metrics are characterised by certain key properties, distinguishing them from the other metric types (counters, instantaneous, and discrete):
Occur at times outside of any monitor tools control, and often have a fine-grained timestamp associated with each event.
Often have parameters associated with the event, which further describe each individual event, as shown in Figure 3.2. Sample write(2) syscall entry point encoding.
May occur in very rapid succession, at rates such that both the collector and monitor sides may not be able to track all events. This property requires the PCP protocol to support the notion of “dropped” or “missed” events.
There may be inherent relationships between events, for example the start and commit (or rollback) of a database transaction could be separate events, linked by a common transaction identifier (which would likely also be one of the parameters to each event). Begin-end and parent-child relationships are relatively common, and these properties require the PCP protocol to support the notion of “flags” that can be associated with events.
These differences aside, the representation of event metrics within PCP shares many aspects of the other metric types - event metrics appear in the Name Space (as do each of the event parameters), each has an associated Performance Metric Identifier and Descriptor, may have an instance domain associated with them, and may be recorded by pmlogger for subsequent replay.
Figure 3.2. Sample write(2) syscall entry point encoding¶
Event metrics and their associated information (parameters, timestamps, flags, and so on) are delivered to monitoring tools alongside sampled metrics as part of the pmResult structure seen previously in Example 3.9. pmResult Structure.
The semantics of pmFetch(3) specifying an event metric PMID are such that all events observed on the collector since the previous fetch (by this specific monitor client) are to transferred to the monitor. Each event will have the metadata described earlier encoded with it (timestamps, flags, and so on) for each event. The encoding of the series of events involves a compound data structure within the pmValueSet associated with the event metric PMID, as illustrated in Figure 3.3. Result Format for Event Performance Metrics from pmFetch.
Figure 3.3. Result Format for Event Performance Metrics from pmFetch¶
At the highest level, the “series of events” is encapsulated within a pmEventArray structure, as in Example 3.10. pmEventArray and pmEventRecord Structures:
Example 3.10. pmEventArray and pmEventRecord Structures
typedef struct {
pmTimeval er_timestamp; /* 2 x 32-bit timestamp format */
unsigned int er_flags; /* event record characteristics */
int er_nparams; /* number of ea_param[] entries */
pmEventParameter er_param[1];
} pmEventRecord;
typedef struct {
unsigned int ea_len : 24; /* bytes for type/len + records */
unsigned int ea_type : 8; /* value type */
int ea_nrecords; /* number of ea_record entries */
pmEventRecord ea_record[1];
} pmEventArray;
Note that in the case of dropped events, the pmEventRecord structure is used to convey the number of events dropped - er_flags is used to indicate the presence of dropped events, and er_nparams is used to hold a count. Unsurprisingly, the parameters (er_param) will be empty in this situation.
The pmEventParameter structure is as follows:
Example 3.11. pmEventParameter Structure
typedef struct {
pmID ep_pmid; /* parameter identifier */
unsigned int ep_type; /* value type */
int ep_len; /* bytes for type/len + vbuf */
/* actual value (vbuf) here */
} pmEventParameter;
3.6.1. Event Monitor Considerations¶
In order to simplify the decoding of event record arrays, the PMAPI provides the pmUnpackEventRecords function for monitor tools. This function is passed a pointer to a pmValueSet associated with an event metric (within a pmResult) from a pmFetch(3). For a given instance of that event metric, it returns an array of “unpacked” pmResult structures for each event.
The control information (flags and optionally dropped events) is included as derived metrics within each result structure. As such, these values can be queried similarly to other metrics, using their names - event.flags and event.missed. Note that these metrics will only exist after the first call to pmUnpackEventRecords.
An example of decoding event metrics in this way is presented in Example 3.12. Unpacking Event Records from an Event Metric pmValueSet:
Example 3.12. Unpacking Event Records from an Event Metric pmValueSet
enum { event_flags = 0, event_missed = 1 };
static char *metadata[] = { "event.flags", "event.missed" };
static pmID metapmid[2];
void dump_event(pmValueSet *vsp, int idx)
{
pmResult **res;
int r, sts, nrecords;
nrecords = pmUnpackEventRecords(vsp, idx, &res);
if (nrecords < 0)
fprintf(stderr, " pmUnpackEventRecords: %s\n", pmErrStr(nrecords));
else
printf(" %d event records\n", nrecords);
if ((sts = pmLookupName(2, &metadata, &metapmid)) < 0) {
fprintf(stderr, "Event metadata error: %s\n", pmErrStr(sts));
exit(1);
}
for (r = 0; r < nrecords; r++)
dump_event_record(res, r);
if (nrecords >= 0)
pmFreeEventResult(res);
}
void dump_event_record(pmResult *res, int r)
{
int p;
pmPrintStamp(stdout, &res[r]->timestamp);
if (res[r]->numpmid == 0)
printf(" ==> No parameters\n");
for (p = 0; p < res[r]->numpmid; p++) {
pmValueSet *vsp = res[r]->vset[p];
if (vsp->numval < 0) {
int error = vsp->numval;
printf("%s: %s\n", pmIDStr(vsp->pmid), pmErrStr(error));
} else if (vsp->pmid == metapmid[event_flags]) {
int flags = vsp->vlist[0].value.lval;
printf(" flags 0x%x (%s)\n", flags, pmEventFlagsStr(flags));
} else if (vsp->pmid == metapmid[event_missed]) {
int count = vsp->vlist[0].value.lval;
printf(" ==> %d missed event records\n", count);
} else {
dump_event_record_parameters(vsp);
}
}
}
void dump_event_record_parameters(pmValueSet *vsp)
{
pmDesc desc;
char *name;
int sts, j;
if ((sts = pmLookupDesc(vsp->pmid, &desc)) < 0) {
fprintf(stderr, "pmLookupDesc: %s\n", pmErrStr(sts));
} else
if ((sts = pmNameID(vsp->pmid, &name)) < 0) {
fprintf(stderr, "pmNameID: %s\n", pmErrStr(sts));
} else {
printf("parameter %s", name);
for (j = 0; j < vsp->numval; j++) {
pmValue *vp = &vsp->vlist[j];
if (vsp->numval > 1) {
printf("[%d]", vp->inst);
pmPrintValue(stdout, vsp->valfmt, desc.type, vp, 1);
putchar('\n');
}
}
free(name);
}
}
3.6.2. Event Collector Considerations¶
There is a feedback mechanism that is inherent in the design of the PCP monitor-collector event metric value exchange, which protects both monitor and collector components from becoming overrun by high frequency event arrivals. It is important that PMDA developers are aware of this mechanism and all of its implications.
Monitor tools can query new event arrival on whatever schedule they choose. There are no guarantees that this is a fixed interval, and no way for the PMDA to attempt to dictate this interval (nor should there be).
As a result, a PMDA that provides event metrics must:
Track individual client connections using the per-client PMDA extensions (PMDA_INTERFACE_5 or later).
Queue events, preferably in a memory-efficient manner, such that each interested monitor tool (there may be more than one) is informed of those events that arrived since their last request.
Control the memory allocated to in-memory event storage. If monitors are requesting new events too slowly, compared to event arrival on the collector, the “missed events” feedback mechanism must be used to inform the monitor. This mechanism is also part of the model by which a PMDA can fix the amount of memory it uses. Once a fixed space is consumed, events can be dropped from the tail of the queue for each client, provided a counter is incremented and the client is subsequently informed.
Note
It is important that PMDAs are part of the performance solution, and not part of the performance problem! With event metrics, this is much more difficult to achieve than with counters or other sampled values.
There is certainly elegance to this approach for event metrics, and the way they dovetail with other, sampled performance metrics is unique to PCP. Notice also how the scheme naturally allows multiple monitor tools to consume the same events, no matter what the source of events is. The downside to this flexibility is increased complexity in the PMDA when event metrics are used.
This complexity comes in the form of event queueing and memory management, as well as per-client state tracking. Routines are available as part of the pcp_pmda library to assist, however - refer to the man page entries for pmdaEventNewQueue(3) and pmdaEventNewClient(3) for further details.
One final set of helper APIs is available to PMDA developers who incorporate event metrics. There is a need to build the pmEventArray structure, introduced in Example 3.10. pmEventArray and pmEventRecord Structures. This can be done directly, or using the helper routine pmdaEventNewArray(3). If the latter, simpler model is chosen, the closely related routines pmdaEventAddRecord, pmdaEventAddParam and pmdaEventAddMissedRecord would also usually be used.
Depending on the nature of the events being exported by a PMDA, it can be desirable to perform filtering of events on the collector system. This reduces the amount of event traffic between monitor and collector systems (which may be filtered further on the monitor system, before presenting results). Some PMDAs have had success using the pmStore(3) mechanism to allow monitor tools to send a filter to the PMDA - using either a special control metric for the store operation, or the event metric itself. The filter sent will depend on the event metric, but it might be a regular expression, or a tracing script, or something else.
This technique has also been used to enable and disable event tracing entirely. It is often appropriate to make use of authentication and user credentials when providing such a facility (PMDA_INTERFACE_6 or later).
3.7. PMAPI Programming Style and Interaction¶
The following sections describe the PMAPI programming style:
Variable length argument and results lists
Python specific issues
PMAPI error handling
3.7.1. Variable Length Argument and Results Lists¶
All arguments and results involving a “list of something” are encoded as an array with an associated argument or function value to identify the number of elements in the array. This encoding scheme avoids both the varargs approach and sentinel-terminated lists. Where the size of a result is known at the time of a call, it is the caller’s responsibility to allocate (and possibly free) the storage, and the called function assumes that the resulting argument is of an appropriate size.
Where a result is of variable size and that size cannot be known in advance (for example, pmGetChildren, pmGetInDom, pmNameInDom, pmNameID, pmLookupText, pmLookupLabels and pmFetch), the underlying implementation uses dynamic allocation through malloc in the called function, with the caller responsible for subsequently calling free to release the storage when no longer required.
In the case of the result from pmFetch, there is a function (pmFreeResult) to release the storage, due to the complexity of the data structure and the need to make multiple calls to free in the correct sequence. Similarly, the pmLookupLabels function has an associated function (pmFreeLabelSets) to release the storage.
As a general rule, if the called function returns an error status, then no allocation is done, the pointer to the variable sized result is undefined, and free, pmFreeLabelSets, or pmFreeResult should not be called.
3.7.2. Python Specific Issues¶
A pcp client may be written in the python language by making use of the python bindings for PMAPI. The bindings use the python ctypes module to provide an interface to the PMAPI C language data structures. The primary imports that are needed by a client are:
cpmapi which provides access to PMAPI constants
import cpmapi as c_api
pmapi which provides access to PMAPI functions and data structures
from pcp import pmapi
pmErr which provides access to the python bindings exception handler
from pcp.pmapi import pmErr
pmgui which provides access to PMAPI record mode functions
from pcp import pmgui
Creating and destroying a PMAPI context in the python environment is done by creating and destroying an object of the pmapi class. This is done in one of two ways, either directly:
context = pmapi.pmContext()
or by automated processing of the command line arguments (refer to the pmGetOptions man page for greater detail).
options = pmapi.pmOptions(...)
context = pmapi.pmContext.fromOptions(options, sys.argv)
Most PMAPI C functions have python equivalents with similar, although not identical, call signatures. Some of the python functions do not return native python types, but instead return native C types wrapped by the ctypes library. In most cases these types are opaque, or nearly so; for example pmid:
pmid = context.pmLookupName("mem.freemem")
desc = context.pmLookupDescs(pmid)
result = context.pmFetch(pmid)
...
See the comparison of a standalone C and python client application in Example 3.25. PMAPI Error Handling.
3.7.3. PMAPI Error Handling¶
Where error conditions may arise, the functions that compose the PMAPI conform to a single, simple error notification scheme, as follows:
The function returns an int. Values greater than or equal to zero indicate no error, and perhaps some positive status: for example, the number of items processed.
Values less than zero indicate an error, as determined by a global table of error conditions and messages.
A PMAPI library function along the lines of strerror is provided to translate error conditions into error messages; see the pmErrStr(3) and pmErrStr_r(3) man pages. The error condition is returned as the function value from a previous PMAPI call; there is no global error indicator (unlike errno). This is to accommodate multi-threaded performance tools.
The available error codes may be displayed with the following command:
pmerr -l
Where possible, PMAPI routines are made as tolerant to failure as possible. In particular, routines which deal with compound data structures - results structures, multiple name lookups in one call and so on, will attempt to return all data that can be returned successfully, and errors embedded in the result where there were (partial) failures. In such cases a negative failure return code from the routine indicates catastrophic failure, otherwise success is returned and indicators for the partial failures are returned embedded in the results.
3.8. PMAPI Procedural Interface¶
The following sections describe all of the PMAPI functions that provide access to the PCP infrastructure on behalf of a client application:
PMAPI Name Space services
PMAPI metric description services
PMAPI instance domain services
PMAPI context services
PMAPI timezone services
PMAPI metrics services
PMAPI fetchgroup services
PMAPI record-mode services
PMAPI archive-specific services
PMAPI time control services
PMAPI ancillary support services
3.8.1. PMAPI Name Space Services¶
The functions described in this section provide Performance Metrics Application Programming Interface (PMAPI) Name Space services.
3.8.1.1. pmGetChildren Function¶
int pmGetChildren(const char*name, char***offspring)
Python:
[name1, name2...] = pmGetChildren(name)
Given a full pathname to a node in the current PMNS, as identified by name, return through offspring a list of the relative names of all the immediate descendents of name in the current PMNS. As a special case, if name is an empty string, (that is, “” but not NULL or (char *)0), the immediate descendents of the root node in the PMNS are returned.
For the python bindings a tuple containing the relative names of all the immediate descendents of name in the current PMNS is returned.
Normally, pmGetChildren returns the number of descendent names discovered, or a value less than zero for an error. The value zero indicates that the name is valid, and associated with a leaf node in the PMNS.
The resulting list of pointers (offspring) and the values (relative metric names) that the pointers reference are allocated by pmGetChildren with a single call to malloc, and it is the responsibility of the caller to issue a free (offspring) system call to release the space when it is no longer required. When the result of pmGetChildren is less than one, offspring is undefined (no space is allocated, and so calling free is counterproductive).
The python bindings return a tuple containing the relative names of all the immediate descendents of name, where name is a full pathname to a node in the current PMNS.
3.8.1.2. pmGetChildrenStatus Function¶
int pmGetChildrenStatus(const char *name, char ***offspring, int **status)
Python:
([name1, name2...],[status1, status2...]) = pmGetChildrenStatus(name)
The pmGetChildrenStatus function is an extension of pmGetChildren that optionally returns status information about each of the descendent names.
Given a fully qualified pathname to a node in the current PMNS, as identified by name, pmGetChildrenStatus returns by means of offspring a list of the relative names of all of the immediate descendent nodes of name in the current PMNS. If name is the empty string (“”), it returns the immediate descendents of the root node in the PMNS.
If status is not NULL, then pmGetChildrenStatus also returns the status of each child by means of status. This refers to either a leaf node (with value PMNS_LEAF_STATUS) or a non-leaf node (with value PMNS_NONLEAF_STATUS).
Normally, pmGetChildrenStatus returns the number of descendent names discovered, or else a value less than zero to indicate an error. The value zero indicates that name is a valid metric name, being associated with a leaf node in the PMNS.
The resulting list of pointers (offspring) and the values (relative metric names) that the pointers reference are allocated by pmGetChildrenStatus with a single call to malloc, and it is the responsibility of the caller to free (offspring) to release the space when it is no longer required. The same holds true for the status array.
The python bindings return a tuple containing the relative names and statuses of all the immediate descendents of name, where name is a full pathname to a node in the current PMNS.
3.8.1.3. pmGetPMNSLocation Function¶
int pmGetPMNSLocation(void)
Python:
int loc = pmGetPMNSLocation()
If an application needs to know where the origin of a PMNS is, pmGetPMNSLocation returns whether it is an archive (PMNS_ARCHIVE), a local PMNS file (PMNS_LOCAL), or a remote PMCD (PMNS_REMOTE). This information may be useful in determining an appropriate error message depending on PMNS location.
The python bindings return whether a PMNS is an archive cpmapi.PMNS_ARCHIVE, a local PMNS file cpmapi.PMNS_LOCAL, or a remote PMCD cpmapi.PMNS_REMOTE. The constants are available by importing cpmapi.
3.8.1.4. pmLoadNameSpace Function¶
int pmLoadNameSpace(const char *filename)
Python:
int status = pmLoadNameSpace(filename)
In the highly unusual situation that an application wants to force using a local Performance Metrics Name Space (PMNS), the application can load the PMNS using pmLoadNameSpace.
The filename argument designates the PMNS of interest. For applications that do not require a tailored Name Space, the special value PM_NS_DEFAULT may be used for filename, to force a default local PMNS to be established. Externally, a PMNS is stored in an ASCII format.
The python bindings load a local tailored Name Space from filename.
Note
Do not use this routine in monitor tools. The distributed PMNS services avoid the need for a local PMNS; so applications should not use pmLoadNameSpace. Without this call, the default PMNS is the one at the source of the performance metrics (PMCD or an archive).
3.8.1.5. pmLookupName Function¶
int pmLookupName(int numpmid, char *namelist[], pmID pmidlist[])
Python:
c_uint pmid [] = pmLookupName("MetricName")
c_uint pmid [] = pmLookupName(("MetricName1", "MetricName2", ...))
Given a list in namelist containing numpmid full pathnames for performance metrics from the current PMNS, pmLookupName returns the list of associated PMIDs through the pmidlist parameter. Invalid metrics names are translated to the error PMID value of PM_ID_NULL.
The result from pmLookupName is the number of names translated in the absence of errors, or an error indication. Note that argument definition and the error protocol guarantee a one-to-one relationship between the elements of namelist and pmidlist; both lists contain exactly numpmid elements.
The python bindings return an array of associated PMIDs corresponding to a tuple of MetricNames. The returned pmid tuple is passed to pmLookupDescs and pmFetch.
3.8.1.6. pmNameAll Function¶
int pmNameAll(pmID pmid, char ***nameset)
Python:
[name1, name2...] = pmNameAll(pmid)
Given a performance metric ID in pmid, pmNameAll determines all the corresponding metric names, if any, in the PMNS, and returns these through nameset.
The resulting list of pointers nameset and the values (relative names) that the pointers reference are allocated by pmNameAll with a single call to malloc. It is the caller’s responsibility to call free and release the space when it is no longer required.
In the absence of errors, pmNameAll returns the number of names in nameset.
For many PMNS instances, there is a 1:1 mapping between a name and a PMID, and under these circumstances, pmNameID provides a simpler interface in the absence of duplicate names for a particular PMID.
The python bindings return a tuple of all metric names having this identical pmid.
3.8.1.7. pmNameID Function¶
int pmNameID(pmID pmid, char **name)
Python:
"metric name" = pmNameID(pmid)
Given a performance metric ID in pmid, pmNameID determines the corresponding metric name, if any, in the current PMNS, and returns this through name.
In the absence of errors, pmNameID returns zero. The name argument is a null byte terminated string, allocated by pmNameID using malloc. It is the caller’s responsibility to call free and release the space when it is no longer required.
The python bindings return a metric name corresponding to a pmid.
3.8.1.8. pmTraversePMNS Function¶
int pmTraversePMNS(const char *name, void (*dometric)(const char *))
Python:
int status = pmTraversePMNS(name, traverse_callback)
The function pmTraversePMNS may be used to perform a depth-first traversal of the PMNS. The traversal starts at the node identified by name –if name is an empty string, the traversal starts at the root of the PMNS. Usually, name would be the pathname of a non-leaf node in the PMNS.
For each leaf node (actual performance metrics) found in the traversal, the user-supplied function dometric is called with the full pathname of that metric in the PMNS as the single argument; this argument is a null byte-terminated string, and is constructed from a buffer that is managed internally to pmTraversePMNS. Consequently, the value is valid only during the call to dometric–if the pathname needs to be retained, it should be copied using strdup before returning from dometric; see the strdup(3) man page.
The python bindings perform a depth first traversal of the PMNS by scanning namespace, depth first, and call a python function traverse_callback for each node.
3.8.1.9. pmUnloadNameSpace Function¶
int pmUnloadNameSpace(void)
Python:
pmUnLoadNameSpace("NameSpace")
If a local PMNS was loaded with pmLoadNameSpace, calling pmUnloadNameSpace frees up the memory associated with the PMNS and force all subsequent Name Space functions to use the distributed PMNS. If pmUnloadNameSpace is called before calling pmLoadNameSpace, it has no effect.
As discussed in Section 3.8.1.4, “pmLoadNameSpace Function” there are few if any situations where clients need to call this routine in modern versions of PCP.
3.8.2. PMAPI Metrics Description Services¶
The functions described in this section provide Performance Metrics Application Programming Interface (PMAPI) metric description services.
3.8.2.1. pmLookupDesc Function¶
int pmLookupDesc(pmID pmid, pmDesc *desc)
Python:
pmDesc* pmdesc = pmLookupDesc(c_uint pmid)
(pmDesc* pmdesc)[] = pmLookupDescs(c_uint pmids[N])
(pmDesc* pmdesc)[] = pmLookupDescs(c_uint pmid)
Given a Performance Metric Identifier (PMID) as pmid, pmLookupDesc returns the associated pmDesc structure through the parameter desc from the current PMAPI context. For more information about pmDesc, see Section 3.4, “Performance Metric Descriptions”.
The python bindings return the metric description structure pmDesc corresponding to pmid. The returned pmdesc is passed to pmExtractValue and pmLookupInDom. The python bindings provide an entry pmLookupDescs that is similar to pmLookupDesc but does a metric description lookup for each element in a PMID array pmids.
3.8.2.2. pmLookupInDomText Function¶
int pmLookupInDomText(pmInDom indom, int level, char **buffer)
Python:
"metric description" = pmGetInDomText(pmDesc pmdesc)
Provided the source of metrics from the current PMAPI context is a host, retrieve descriptive text about the performance metrics instance domain identified by indom.
The level argument should be PM_TEXT_ONELINE for a one-line summary, or PM_TEXT_HELP for a more verbose description suited to a help dialogue. The space pointed to by buffer is allocated in pmLookupInDomText with malloc, and it is the responsibility of the caller to free unneeded space; see the malloc(3) and free(3) man pages.
The help text files used to implement pmLookupInDomText are often created using newhelp and accessed by the appropriate PMDA response to requests forwarded to the PMDA by PMCD. Further details may be found in Section 2.4.4, “PMDA Help Text” .
The python bindings lookup the description text about the performance metrics pmDesc pmdesc. The default is a one line summary; for a more verbose description add an optional second parameter cpmapi.PM_TEXT_HELP. The constant is available by importing cpmapi.
3.8.2.3. pmLookupText Function¶
int pmLookupText(pmID pmid, int level, char **buffer)
Python:
"metric description" = pmLookupText(c_uint pmid)
Retrieve descriptive text about the performance metric identified by pmid. The argument level should be PM_TEXT_ONELINE for a one-line summary, or PM_TEXT_HELP for a more verbose description, suited to a help dialogue.
The space pointed to by buffer is allocated in pmLookupText with malloc, and it is the responsibility of the caller to free the space when it is no longer required; see the malloc(3) and free(3) man pages.
The help text files used to implement pmLookupText are created using newhelp and accessed by the appropriate PMDA in response to requests forwarded to the PMDA by PMCD. Further details may be found in Section 2.4.4, “PMDA Help Text”.
The python bindings lookup the description text about the performance metrics pmID pmid. The default is a one line summary; for a more verbose description add an optional second parameter cpmapi.PM_TEXT_HELP. The constant is available by importing cpmapi.
3.8.2.4. pmLookupLabels Function¶
int pmLookupLabels(pmID pmid, pmLabelSet **labelsets)
Python:
(pmLabelSet* pmlabelset)[] pmLookupLabels(c_uint pmid)
Retrieve name:value pairs providing additional identity and descriptive metadata about the performance metric identified by pmid.
The space pointed to by labelsets is allocated in pmLookupLabels with potentially multiple calls to malloc and it is the responsibility of the caller to pmFreeLabelSets the space when it is no longer required; see the malloc(3) and pmFreeLabelSets(3) man pages.
Additional helper interfaces are also available, used internally by pmLookupLabels and to help with post-processing of labelsets. See the pmLookupLabels(3) and pmMergeLabelSets(3) man pages.
3.8.3. PMAPI Instance Domain Services¶
The functions described in this section provide Performance Metrics Application Programming Interface (PMAPI) instance domain services.
3.8.3.1. pmGetInDom Function¶
int pmGetInDom(pmInDom indom, int **instlist, char ***namelist)
Python:
([instance1, instance2...] [name1, name2...]) pmGetInDom(pmDesc pmdesc)
In the current PMAPI context, locate the description of the instance domain indom, and return through instlist the internal instance identifiers for all instances, and through namelist the full external identifiers for all instances. The number of instances found is returned as the function value (or less than zero to indicate an error).
The resulting lists of instance identifiers (instlist and namelist), and the names that the elements of namelist point to, are allocated by pmGetInDom with two calls to malloc, and it is the responsibility of the caller to use free (instlist) and free (namelist) to release the space when it is no longer required. When the result of pmGetInDom is less than one, both instlist and namelist are undefined (no space is allocated, and so calling free is a bad idea); see the malloc(3) and free(3) man pages.
The python bindings return a tuple of the instance identifiers and instance names for an instance domain pmdesc.
3.8.3.2. pmLookupInDom Function¶
int pmLookupInDom(pmInDom indom, const char *name)
Python:
int instid = pmLookupInDom(pmDesc pmdesc, "Instance")
For the instance domain indom, in the current PMAPI context, locate the instance with the external identification given by name, and return the internal instance identifier.
The python bindings return the instance id corresponding to “Instance” in the instance domain pmdesc.
3.8.3.3. pmNameInDom Function¶
int pmNameInDom(pmInDom indom, int inst, char **name)
Python:
"instance id" = pmNameInDom(pmDesc pmdesc, c_uint instid)
For the instance domain indom, in the current PMAPI context, locate the instance with the internal instance identifier given by inst, and return the full external identification through name. The space for the value of name is allocated in pmNameInDom with malloc, and it is the responsibility of the caller to free the space when it is no longer required; see the malloc(3) and free(3) man pages.
The python bindings return the text name of an instance corresponding to an instance domain pmdesc with instance identifier instid.
3.8.4. PMAPI Context Services¶
Table 3.1. Context Components of PMAPI Functions shows which of the three components of a PMAPI context (metrics source, instance profile, and collection time) are relevant for various PMAPI functions. Those PMAPI functions not shown in this table either manipulate the PMAPI context directly, or are executed independently of the current PMAPI context.
Table 3.1. Context Components of PMAPI Functions
Function name |
Metrics Source |
Instance Profile |
Collection Time |
Notes |
pmAddProfile |
Yes |
Yes |
||
pmDelProfile |
Yes |
Yes |
||
pmDupContext |
Yes |
Yes |
Yes |
|
pmFetch |
Yes |
Yes |
Yes |
|
pmFetchArchive |
Yes |
Yes |
( 1 ) |
|
pmGetArchiveEnd |
Yes |
( 1 ) |
||
pmGetArchiveLabel |
Yes |
( 1 ) |
||
pmGetChildren |
Yes |
|||
pmGetChildrenStatus |
Yes |
|||
pmGetContextHostName |
Yes |
|||
pmGetPMNSLocation |
Yes |
|||
pmGetInDom |
Yes |
Yes |
( 2 ) |
|
pmGetInDomArchive |
Yes |
( 1 ) |
||
pmLookupDesc |
Yes |
( 3 ) |
||
pmLookupInDom |
Yes |
Yes |
( 2 ) |
|
pmLookupInDomArchive |
Yes |
( 1,2 ) |
||
pmLookupInDomText |
Yes |
|||
pmLookupLabels |
Yes |
|||
pmLookupName |
Yes |
|||
pmLookupText |
Yes |
|||
pmNameAll |
Yes |
|||
pmNameID |
Yes |
|||
pmNameInDom |
Yes |
Yes |
( 2 ) |
|
pmNameInDomArchive |
Yes |
( 1,2 ) |
||
pmSetMode |
Yes |
Yes |
||
pmStore |
Yes |
( 4 ) |
||
pmTraversePMNS |
Yes |
Notes:
Operation supported only for PMAPI contexts where the source of metrics is an archive.
A specific instance domain is included in the arguments to these functions, and the result is independent of the instance profile for any PMAPI context.
The metadata that describes a performance metric is sensitive to the source of the metrics, but independent of any instance profile and of the collection time.
This operation is supported only for contexts where the source of the metrics is a host. Further, the instance identifiers are included in the argument to the function, and the effects upon the current values of the metrics are immediate (retrospective changes are not allowed). Consequently, from the current PMAPI context, neither the instance profile nor the collection time influence the result of this function.
3.8.4.1. pmNewContext Function¶
int pmNewContext(int type, const char *name)
The pmNewContext function may be used to establish a new PMAPI context. The source of metrics is identified by name, and may be a host specification (type is PM_CONTEXT_HOST) or a comma-separated list of names referring to a set of archive logs (type is PM_CONTEXT_ARCHIVE). Each element of the list may either be the base name common to all of the physical files of an archive log or the name of a directory containing archive logs.
A host specification usually contains a simple hostname, an internet address (IPv4 or IPv6), or the path to the PMCD Unix domain socket. It can also specify properties of the connection to PMCD, such as the protocol to use (secure and encrypted, or native) and whether PMCD should be reached via a pmproxy host. Various other connection attributes, such as authentication information (user name, password, authentication method, and so on) can also be specified. Further details can be found in the PCPIntro(3) man page, and the companion Performance Co-Pilot Tutorials and Case Studies document.
In the case where type is PM_CONTEXT_ARCHIVE, there are some restrictions on the archives within the specified set:
The archives must all have been generated on the same host.
The archives must not overlap in time.
The archives must all have been created using the same time zone.
The pmID of each metric should be the same in all of the archives. Multiple pmIDs are currently tolerated by using the first pmID defined for each metric and ignoring subsequent pmIDs.
The type of each metric must be the same in all of the archives.
The semantics of each metric must be the same in all of the archives.
The units of each metric must be the same in all of the archives.
The instance domain of each metric must be the same in all of the archives.
In the case where type is PM_CONTEXT_LOCAL, name is ignored, and the context uses a stand-alone connection to the PMDA methods used by PMCD. When this
type of context is in effect, the range of accessible performance metrics is constrained to DSO PMDAs listed in the pmcd configuration file ${PCP_PMCDCONF_PATH}.
The reason this is done, as opposed to all of the DSO PMDAs found below ${PCP_PMDAS_DIR} for example, is that DSO PMDAs listed there are very likely to have
their metric names reflected in the local Name Space file, which will be loaded for this class of context.
The initial instance profile is set up to select all instances in all instance domains, and the initial collection time is the current time at the time of each request for a host, or the time at the start of the first log for a set of archives. In the case of archives, the initial collection time results in the earliest set of metrics being returned from the set of archives at the first pmFetch.
Once established, the association between a PMAPI context and a source of metrics is fixed for the life of the context; however, functions are provided to independently manipulate both the instance profile and the collection time components of a context.
The function returns a “handle” that may be used in subsequent calls to pmUseContext. This new PMAPI context stays in effect for all subsequent context sensitive calls across the PMAPI until another call to pmNewContext is made, or the context is explicitly changed with a call to pmDupContext or pmUseContext.
For the python bindings creating and destroying a PMAPI context is done by creating and destroying an object of the pmapi class.
3.8.4.2. pmDestroyContext Function¶
int pmDestroyContext(int handle)
The PMAPI context identified by handle is destroyed. Typically, this implies terminating a connection to PMCD or closing an archive file, and orderly clean-up. The PMAPI context must have been previously created using pmNewContext or pmDupContext.
On success, pmDestroyContext returns zero. If handle was the current PMAPI context, then the current context becomes undefined. This means the application must explicitly re-establish a valid PMAPI context with pmUseContext, or create a new context with pmNewContext or pmDupContext, before the next PMAPI operation requiring a PMAPI context.
For the python bindings creating and destroying a PMAPI context is done by creating and destroying an object of the pmapi class.
3.8.4.3. pmDupContext Function¶
int pmDupContext(void)
Replicate the current PMAPI context (source, instance profile, and collection time). This function returns a handle for the new context, which may be used with subsequent calls to pmUseContext. The newly replicated PMAPI context becomes the current context.
3.8.4.4. pmUseContext Function¶
int pmUseContext(int handle)
Calling pmUseContext causes the current PMAPI context to be set to the context identified by handle. The value of handle must be one returned from an earlier call to pmNewContext or pmDupContext.
Below the PMAPI, all contexts used by an application are saved in their most recently modified state, so pmUseContext restores the context to the state it was in the last time the context was used, not the state of the context when it was established.
3.8.4.5. pmWhichContext Function¶
int pmWhichContext(void)
Python:
int ctx_idx = pmWhichContext()
Returns the handle for the current PMAPI context (source, instance profile, and collection time).
The python bindings return the handle of the current PMAPI context.
3.8.4.6. pmAddProfile Function¶
int pmAddProfile(pmInDom indom, int numinst, int instlist[])
Python:
int status = pmAddProfile(pmDesc pmdesc, [c_uint instid])
Add new instance specifications to the instance profile of the current PMAPI context. At its simplest, instances identified by the instlist argument for the indom instance domain are added to the instance profile. The list of instance identifiers contains numinst values.
If indom equals PM_INDOM_NULL, or numinst is zero, then all instance domains are selected. If instlist is NULL, then all instances are selected. To enable all available instances in all domains, use this syntax:
pmAddProfile(PM_INDOM_NULL, 0, NULL).
The python bindings add the list of instances instid to the instance profile of the instance pmdesc.
3.8.4.7. pmDelProfile Function¶
int pmDelProfile(pmInDom indom, int numinst, int instlist[])
Python:
int status = pmDelProfile(pmDesc pmdesc, c_uint instid)
int status = pmDelProfile(pmDesc pmdesc, [c_uint instid])
Delete instance specifications from the instance profile of the current PMAPI context. In the simplest variant, the list of instances identified by the instlist argument for the indom instance domain is removed from the instance profile. The list of instance identifiers contains numinst values.
If indom equals PM_INDOM_NULL, then all instance domains are selected for deletion. If instlist is NULL, then all instances in the selected domains are removed from the profile. To disable all available instances in all domains, use this syntax:
pmDelProfile(PM_INDOM_NULL, 0, NULL)
The python bindings delete the list of instances instid from the instance profile of the instance domain pmdesc.
3.8.4.8. pmSetMode Function¶
int pmSetMode(int mode, const struct timeval *when, int delta)
Python:
int status = pmSetMode(mode, timeVal timeval, int delta)
This function defines the collection time and mode for accessing performance metrics and metadata in the current PMAPI context. This mode affects the semantics of subsequent calls to the following PMAPI functions: pmFetch, pmFetchArchive, pmLookupDesc, pmGetInDom, pmLookupInDom , and pmNameInDom.
The pmSetMode function requires the current PMAPI context to be of type PM_CONTEXT_ARCHIVE.
The when parameter defines a time origin, and all requests for metadata (metrics descriptions and instance identifiers from the instance domains) are processed to reflect the state of the metadata as of the time origin. For example, use the last state of this information at, or before, the time origin.
If the mode is PM_MODE_INTERP then, in the case of pmFetch, the underlying code uses an interpolation scheme to compute the values of the metrics from the values recorded for times in the proximity of the time origin.
If the mode is PM_MODE_FORW, then, in the case of pmFetch, the collection of recorded metric values is scanned forward, until values for at least one of the requested metrics is located after the time origin. Then all requested metrics stored in the PCP archive at that time are returned with a corresponding time stamp. This is the default mode when an archive context is first established with pmNewContext.
If the mode is PM_MODE_BACK, then the situation is the same as for PM_MODE_FORW, except a pmFetch is serviced by scanning the collection of recorded metrics backward for metrics before the time origin.
After each successful pmFetch, the time origin is reset to the time stamp returned through the pmResult.
The pmSetMode parameter delta defines an additional number of time unit that should be used to adjust the time origin (forward or backward) after the new time origin from the pmResult has been determined. This is useful when moving through archives with a mode of PM_MODE_INTERP. The high-order bits of the mode parameter field is also used to optionally set the units of time for the delta field. To specify the units of time, use the PM_XTB_SET macro with one of the values PM_TIME_NSEC, PM_TIME_MSEC, PM_TIME_SEC, or so on as follows:
PM_MODE_INTERP | PM_XTB_SET(PM_TIME_XXXX)
If no units are specified, the default is to interpret delta as milliseconds.
Using these mode options, an application can implement replay, playback, fast forward, or reverse for performance metric values held in a set of PCP archive logs by alternating calls to pmSetMode and pmFetch.
In Example 3.13. Dumping Values in Temporal Sequence, the code fragment may be used to dump only those values stored in correct temporal sequence, for the specified performance metric my.metric.name:
Example 3.13. Dumping Values in Temporal Sequence
int sts;
pmID pmid;
char *name = “my.metric.name”;
sts = pmNewContext(PM_CONTEXT_ARCHIVE, “myarchive”);
sts = pmLookupName(1, &name, &pmid);
for ( ; ; ) {
sts = pmFetch(1, &pmid, &result);
if (sts < 0)
break;
/* dump value(s) from result->vset[0]->vlist[] */
pmFreeResult(result);
}
Alternatively, the code fragment in Example 3.14. Replaying Interpolated Metrics may be used to replay interpolated metrics from an archive in reverse chronological order, at ten-second intervals (of recorded time):
Example 3.14. Replaying Interpolated Metrics
int sts;
pmID pmid;
char *name = “my.metric.name”;
struct timeval endtime;
sts = pmNewContext(PM_CONTEXT_ARCHIVE, “myarchive”);
sts = pmLookupName(1, &name, &pmid);
sts = pmGetArchiveEnd(&endtime);
sts = pmSetMode(PM_MODE_INTERP, &endtime, -10000);
while (pmFetch(1, &pmid, &result) != PM_ERR_EOL) {
/*
* process interpolated metric values as of result->timestamp
*/
pmFreeResult(result);
}
The python bindings define the collection time and mode for reading archive files. mode can be one of: c_api.PM_MODE_LIVE, c_api.PM_MODE_INTERP, c_api.FORW, c_api.BACK. wjocj are available by importing cpmapi.
3.8.4.9. pmReconnectContext Function¶
int pmReconnectContext(int handle)
Python:
int status = pmReconnectContext()
As a result of network, host, or PMCD (Performance Metrics Collection Daemon) failure, an application’s connection to PMCD may be established and then lost.
The function pmReconnectContext allows an application to request that the PMAPI context identified by handle be re-established, provided the associated PMCD is accessible.
Note
handle may or may not be the current context.
To avoid flooding the system with reconnect requests, pmReconnectContext attempts a reconnection only after a suitable delay from the previous attempt. This imposed restriction on the reconnect re-try time interval uses a default exponential back-off so that the initial delay is 5 seconds after the first unsuccessful attempt, then 10 seconds, then 20 seconds, then 40 seconds, and then 80 seconds thereafter. The intervals between reconnection attempts may be modified using the environment variable PMCD_RECONNECT_TIMEOUT and the time to wait before an attempted connection is deemed to have failed is controlled by the PMCD_CONNECT_TIMEOUT environment variable; see the PCPIntro(1) man page.
If the reconnection succeeds, pmReconnectContext returns handle. Note that even in the case of a successful reconnection, pmReconnectContext does not change the current PMAPI context.
The python bindings reestablish the connection for the context.
3.8.4.10. pmGetContextHostName Function¶
const char *pmGetContextHostName(int id)
char *pmGetContextHostName_r(int id, char *buf, int buflen)
Python:
"hostname" = pmGetContextHostName()
Given a valid PCP context identifier previously created with pmNewContext or pmDupContext, the pmGetContextHostName function provides a possibility to retrieve a host name associated with a context regardless of the context type.
This function will use the pmcd.hostname metric if it is available, and so is able to provide an accurate hostname in the presence of connection tunnelling and port forwarding.
If id is not a valid PCP context identifier, this function returns a zero length string and therefore never fails.
In the case of pmGetContextHostName, the string value is held in a single static buffer, so concurrent calls may not produce the desired results. The pmGetContextHostName_r function allows a buffer and length to be passed in, into which the message is stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings query the current context hostname.
3.8.5. PMAPI Timezone Services¶
The functions described in this section provide Performance Metrics Application Programming Interface (PMAPI) timezone services.
3.8.5.1. pmNewContextZone Function¶
int pmNewContextZone(void)
Python:
pmNewContextZone()
If the current PMAPI context is an archive, the pmNewContextZone function uses the timezone from the archive label record in the first archive of the set to set the current reporting timezone. The current reporting timezone affects the timezone used by pmCtime and pmLocaltime.
If the current PMAPI context corresponds to a host source of metrics, pmNewContextZone executes a pmFetch to retrieve the value for the metric pmcd.timezone and uses that to set the current reporting timezone.
In both cases, the function returns a value to identify the current reporting timezone that may be used in a subsequent call to pmUseZone to restore this reporting timezone.
PM_ERR_NOCONTEXT indicates the current PMAPI context is not valid. A return value less than zero indicates a fatal error from a system call, most likely malloc.
3.8.5.2. pmNewZone Function¶
int pmNewZone(const char *tz)
Python:
int tz_handle = pmNewZone(int tz)
The pmNewZone function sets the current reporting timezone, and returns a value that may be used in a subsequent call to pmUseZone to restore this reporting timezone. The current reporting timezone affects the timezone used by pmCtime and pmLocaltime.
The tz argument defines a timezone string, in the format described for the TZ environment variable. See the environ(7) man page.
A return value less than zero indicates a fatal error from a system call, most likely malloc.
The python bindings create a new zone handle and set reporting timezone for the timezone defined by tz.
3.8.5.3. pmUseZone Function¶
int pmUseZone(const int tz_handle)
Python:
int status = pmUseZone(int tz_handle)
In the pmUseZone function, tz_handle identifies a reporting timezone as previously established by a call to pmNewZone or pmNewContextZone, and this becomes the current reporting timezone. The current reporting timezone effects the timezone used by pmCtime and pmLocaltime).
A return value less than zero indicates the value of tz_handle is not legal.
The python bindings set the current reporting timezone defined by timezone tz_handle.
3.8.5.4. pmWhichZone Function¶
int pmWhichZone(char **tz)
Python:
"zone string" = pmWhichZone()
The pmWhichZone function returns the handle of the current timezone, as previously established by a call to pmNewZone or pmNewContextZone. If the call is successful (that is, there exists a current reporting timezone), a non-negative integer is returned and tz is set to point to a static buffer containing the timezone string itself. The current reporting timezone effects the timezone used by pmCtime and pmLocaltime.
A return value less than zero indicates there is no current reporting timezone.
The python bindings return the current reporting timezone.
3.8.6. PMAPI Metrics Services¶
The functions described in this section provide Performance Metrics Application Programming Interface (PMAPI) metrics services.
3.8.6.1. pmFetch Function¶
int pmFetch(int numpmid, pmID pmidlist[], pmResult **result)
Python:
pmResult* pmresult = pmFetch(c_uint pmid[])
The most common PMAPI operation is likely to be calls to pmFetch, specifying a list of PMIDs (for example, as constructed by pmLookupName) through pmidlist and numpmid. The call to pmFetch is executed in the context of a source of metrics, instance profile, and collection time, previously established by calls to the functions described in Section 3.8.4, “PMAPI Context Services”.
The principal result from pmFetch is returned as a tree structured result, described in the Section 3.5, “Performance Metrics Values”.
If one value (for example, associated with a particular instance) for a requested metric is unavailable at the requested time, then there is no associated pmValue structure in the result. If there are no available values for a metric, then numval is zero and the associated pmValue[] instance is empty; valfmt is undefined in these circumstances, but pmid is correctly set to the PMID of the metric with no values.
If the source of the performance metrics is able to provide a reason why no values are available for a particular metric, this reason is encoded as a standard error code in the corresponding numval; see the pmerr(1) and pmErrStr(3) man pages. Since all error codes are negative, values for a requested metric are unavailable if numval is less than or equal to zero.
The argument definition and the result specifications have been constructed to ensure that for each PMID in the requested pmidlist there is exactly one pmValueSet in the result, and that the PMIDs appear in exactly the same sequence in both pmidlist and result. This makes the number and order of entries in result completely deterministic, and greatly simplifies the application programming logic after the call to pmFetch.
The result structure returned by pmFetch is dynamically allocated using one or more calls to malloc and specialized allocation strategies, and should be released when no longer required by calling pmFreeResult. Under no circumstances should free be called directly to release this space.
As common error conditions are encoded in the result data structure, only serious events (such as loss of connection to PMCD, malloc failure, and so on) would cause an error value to be returned by pmFetch. Otherwise, the value returned by the pmFetch function is zero.
In Example 3.15. PMAPI Metrics Services, the code fragment dumps the values (assumed to be stored in the lval element of the pmValue structure) of selected performance metrics once every 10 seconds:
Example 3.15. PMAPI Metrics Services
int i, j, sts;
pmID pmidlist[10];
pmResult *result;
time_t now;
/* set up PMAPI context, numpmid and pmidlist[] ... */
while ((sts = pmFetch(10, pmidlist, &result)) >= 0) {
now = (time_t)result->timestamp.tv_sec;
printf("\n@ %s", ctime(&now));
for (i = 0; i < result->numpmid; i++) {
printf("PMID: %s", pmIDStr(result->vset[i]->pmid));
for (j = 0; j < result->vset[i]->numval; j++) {
printf(" 0x%x", result->vset[i]->vlist[j].value.lval);
putchar('\n');
}
}
pmFreeResult(result);
sleep(10);
}
Note
If a response is not received back from PMCD within 10 seconds, the pmFetch times out and returns PM_ERR_TIMEOUT. This is most likely to occur when the PMAPI client and PMCD are communicating over a slow network connection, but may also occur when one of the hosts is extremely busy. The time out period may be modified using the PMCD_REQUEST_TIMEOUT environment variable; see the PCPIntro(1) man page.
The python bindings fetch a pmResult corresponding to a pmid list, which is returned from pmLookupName. The returned pmresult is passed to pmExtractValue.
3.8.6.2. pmFreeResult Function¶
void pmFreeResult(pmResult *result)
Python:
pmFreeResult(pmResult* pmresult)
Release the storage previously allocated for a result by pmFetch.
THe python bindings free a pmresult previously allocated by pmFetch.
3.8.6.3. pmStore Function¶
int pmStore(const pmResult *request)
Python:
pmResult* pmresult = pmStore(pmResult* pmresult)
In some special cases it may be helpful to modify the current values of performance metrics in one or more underlying domains, for example to reset a counter to zero, or to modify a metric, which is a control variable within a Performance Metric Domain.
The pmStore function is a lightweight inverse of pmFetch. The caller must build the pmResult data structure (which could have been returned from an earlier pmFetch call) and then call pmStore. It is an error to pass a request to pmStore in which the numval field within any of the pmValueSet structure has a value less than one.
The current PMAPI context must be one with a host as the source of metrics, and the current value of the nominated metrics is changed. For example, pmStore cannot be used to make retrospective changes to information in a PCP archive log.
3.8.7. PMAPI Fetchgroup Services¶
The fetchgroup functions implement a registration-based mechanism to fetch groups of performance metrics, including automation for general unit, rate, type conversions and convenient instance and value encodings. They constitute a powerful and compact alternative to the classic Performance Metrics Application Programming Interface (PMAPI) sequence of separate lookup, check, fetch, iterate, extract, and convert functions.
A fetchgroup consists of a PMAPI context and a list of metrics that the application is interested in fetching. For each metric of interest, a conversion specification and a destination pmAtomValue pointer is given. Then, at each subsequent fetchgroup-fetch operation, all metrics are fetched, decoded/converted, and deposited in the desired field of the destination pmAtomValues. See Example 3.18. pmAtomValue Structure for more on that data type. Similarly, a per-metric-instance status value is optionally available for detailed diagnostics reflecting fetch/conversion.
The pmfetchgroup(3) man pages give detailed information on the C API; we only list some common cases here. The simplified Python binding to the same API is summarized below. One difference is that runtime errors in C are represented by status integers, but in Python are mapped to pmErr exceptions. Another is that supplying metric type codes are mandatory in the C API but optional in Python, since the latter language supports dynamic typing. Another difference is Python’s wrapping of output metric values in callable “holder” objects. We demonstrate all of these below.
3.8.7.1. Fetchgroup setup¶
To create a fetchgroup and its private PMAPI context, the pmCreateFetchGroup function is used, with parameters similar to pmNewContext (see Section 3.8.4.1, “pmNewContext Function”).
int sts;
pmFG fg;
sts = pmCreateFetchGroup(& fg, PM_CONTEXT_ARCHIVE, "./foo.meta");
assert(sts == 0);
Python
fg = pmapi.fetchgroup(c_api.PM_CONTEXT_ARCHIVE, './foo.meta')
If special PMAPI query, PMNS enumeration, or configuration upon the context is needed, the private context may be carefully accessed.
int ctx = pmGetFetchGroupContext(fg);
sts = pmUseContext(ctx);
assert(sts == 0);
sts = pmSetMode(...);
Python
ctx = fg.get_context()
ctx.pmSetMode(...)
A fetchgroup is born empty. It needs to be extended with metrics to read. Scalars are easy. We specify the metric name, an instance-domain instance if necessary, a unit-scaling and/or rate-conversion directive if desired, and a type code (see Example 3.2. pmDesc Structure). In C, the value destination is specified by pointer. In Python, a value-holder is returned.
static pmAtomValue ncpu, loadavg, idle;
sts = pmExtendFetchGroup_item(fg, "hinv.ncpu", NULL, NULL,
& ncpu, PM_TYPE_32, NULL);
assert (sts == 0);
sts = pmExtendFetchGroup_item(fg, "kernel.all.load", "5 minute", NULL,
& loadavg, PM_TYPE_DOUBLE, NULL);
assert (sts == 0);
sts = pmExtendFetchGroup_item(fg, "kernel.all.cpu.idle", NULL, "s/100s",
& idle, PM_TYPE_STRING, NULL);
assert (sts == 0);
Python
ncpu = fg.extend_item('hinv.cpu')
loadavg = fg.extend_item('kernel.all.load', instance='5 minute')
idle = fg.extend_item('kernel.all.cpu.idle, scale='s/100s')
Registering metrics with whole instance domains are also possible; these result in a vector of pmAtomValue instances, instance names and codes, and status codes, so the fetchgroup functions take more optional parameters. In Python, a value-holder-iterator object is returned.
enum { max_disks = 100 };
static unsigned num_disks;
static pmAtomValue disk_reads[max_disks];
static int disk_read_stss[max_disks];
static char *disk_names[max_disks];
sts = pmExtendFetchGroup_indom(fg, "disk.dm.read", NULL,
NULL, disk_names, disk_reads, PM_TYPE_32,
disk_read_stss, max_disks, & num_disks,
NULL);
Python
values = fg.extend_indom('disk.dm.read')
Registering interest in the future fetch-operation timestamp is also possible. In python, a datetime-holder object is returned.
struct timeval tv;
sts = pmExtendFetchGroup_timestamp(fg, & tv);
Python
tv = fg.extend_timestamp()
3.8.7.2. Fetchgroup operation¶
Now it’s time for the program to process the metrics. In the C API, each metric value is put into status integers (if requested), and one field of the pmAtomValue union - whichever was requested with the PM_TYPE_* code. In the Python API, each metric value is accessed by calling the value-holder objects.
sts = pmFetchGroup(fg);
assert (sts == 0);
printf("%s", ctime(& tv.tv_sec));
printf("#cpus: %d, loadavg: %g, idle: %s\n", ncpu.l, loadavg.d, idle.cp);
for (i=0; i<num_disks; i++)
if (disk_read_stss[i] == 0)
printf("disk %s reads %d\n", disk_names[i], disk_reads[i].l);
Python
fg.fetch()
print(tv())
print("#cpus: %d, loadavg: %g, idle: %d\n" % (ncpu(), loadavg(), idle()))
for icode, iname, value in values():
print('disk %s reads %d' % (iname, value()))
The program may fetch and process the values only once, or in a loop. The program need not - must not - modify or free any of the output values/pointers supplied by the fetchgroup functions.
3.8.7.3. Fetchgroup shutdown¶
Should the program wish to shut down a fetchgroup explicitly, thereby closing the private PMAPI context, there is a function for that.
sts = pmDestroyFetchGroup(fg);
Python
del fg # or nothing
3.8.8. PMAPI Record-Mode Services¶
The functions described in this section provide Performance Metrics Application Programming Interface (PMAPI) record-mode services. These services allow a monitor tool to establish connections to pmlogger co-processes, which they create and control for the purposes of recording live performance data from (possibly) multiple hosts. Since pmlogger records for one host only, these services can administer a group of loggers, and set up archive folios to track the logs. Tools like pmafm can subsequently use those folios to replay recorded data with the initiating tool. pmchart uses these concepts when providing its Record mode functionality.
3.8.8.1. pmRecordAddHost Function¶
int pmRecordAddHost(const char *host, int isdefault, pmRecordHost **rhp)
Python:
(int status, pmRecordHost* rhp) = pmRecordAddHost("host string", 1, "configure string")
The pmRecordAddHost function adds hosts once pmRecordSetup has established a new recording session. The pmRecordAddHost function along with the pmRecordSetup and pmRecordControl functions are used to create a PCP archive.
pmRecordAddHost is called for each host that is to be included in the recording session. A new pmRecordHost structure is returned via rhp. It is assumed that PMCD is running on the host as this is how pmlogger retrieves the required performance metrics.
If this host is the default host for the recording session, isdefault is nonzero. This ensures that the corresponding archive appears first in the PCP archive folio. Hence the tools used to replay the archive folio make the correct determination of the archive associated with the default host. At most one host per recording session may be nominated as the default host.
The calling application writes the desired pmlogger configuration onto the stdio stream returned via the f_config field in the pmRecordHost structure.
pmRecordAddHost returns 0 on success and a value less than 0 suitable for decoding with pmErrStr on failure. The value EINVAL has the same interpretation as errno being set to EINVAL.
3.8.8.2. pmRecordControl Function¶
int pmRecordControl(pmRecordHost *rhp, int request, const char *options)
Python:
int status = pmRecordControl("host string", 1, "configure string")
Arguments may be optionally added to the command line that is used to launch pmlogger by calling the pmRecordControl function with a request of PM_REC_SETARG. The pmRecordControl along with the pmRecordSetup and pmRecordAddHost functions are used to create a PCP archive.
The argument is passed via options and one call to pmRecordControl is required for each distinct argument. An argument may be added for a particular pmlogger instance identified by rhp. If the rhp argument is NULL, the argument is added for all pmlogger instances that are launched in the current recording session.
Independent of any calls to pmRecordControl with a request of PM_REC_SETARG, each pmlogger instance is automatically launched with the following arguments: -c, -h, -l, -x, and the basename for the PCP archive log.
To commence the recording session, call pmRecordControl with a request of PM_REC_ON, and rhp must be NULL. This launches one pmlogger process for each host in the recording session and initializes the fd_ipc, logfile, pid, and status fields in the associated pmRecordHost structure(s).
To terminate a pmlogger instance identified by rhp, call pmRecordControl with a request of PM_REC_OFF. If the rhp argument to pmRecordControl is NULL, the termination request is broadcast to all pmlogger processes in the current recording session. An informative dialogue is generated directly by each pmlogger process.
To display the current status of the pmlogger instance identified by rhp, call pmRecordControl with a request of PM_REC_STATUS. If the rhp argument to pmRecordControl is NULL, the status request is broadcast to all pmlogger processes in the current recording session. The display is generated directly by each pmlogger process.
To detach a pmlogger instance identified by rhp, allow it to continue independent of the application that launched the recording session and call pmRecordControl with a request of PM_REC_DETACH. If the rhp argument to pmRecordControl is NULL, the detach request is broadcast to all pmlogger processes in the current recording session.
pmRecordControl returns 0 on success and a value less than 0 suitable for decoding with pmErrStr on failure. The value EINVAL has the same interpretation as errno being set to EINVAL.
pmRecordControl returns PM_ERR_IPC if the associated pmlogger process has already exited.
3.8.8.3. pmRecordSetup Function¶
FILE *pmRecordSetup(const char *folio, const char *creator, int replay)
Python:
int status = pmRecordSetup("folio string", "creator string", int replay)
The pmRecordSetup function along with the pmRecordAddHost and pmRecordControl functions may be used to create a PCP archive on the fly to support record-mode services for PMAPI client applications.
Each record mode session involves one or more PCP archive logs; each is created using a dedicated pmlogger process, with an overall Archive Folio format as understood by the pmafm command, to name and collect all of the archive logs associated with a single recording session.
The pmRecordHost structure is used to maintain state information between the creator of the recording session and the associated pmlogger process(es). The structure, shown in Example 3.16. pmRecordHost Structure, is defined as:
Example 3.16. pmRecordHost Structure
typedef struct {
FILE *f_config; /* caller writes pmlogger configuration here */
int fd_ipc; /* IPC channel to pmlogger */
char *logfile; /* full pathname for pmlogger error logfile */
pid_t pid; /* process id for pmlogger */
int status; /* exit status, -1 if unknown */
} pmRecordHost;
In Procedure 3.1. Creating a Recording Session, the functions are used in combination to create a recording session.
Procedure 3.1. Creating a Recording Session
Call pmRecordSetup to establish a new recording session. A new Archive Folio is created using the name folio. If the folio file or directory already exists, or if it cannot be created, this is an error. The application that is creating the session is identified by creator (most often this would be the same as the global PMAPI application name, as returned pmGetProgname()). If the application knows how to create its own configuration file to replay the recorded session, replay should be nonzero. The pmRecordSetup function returns a stdio stream onto which the application writes the text of any required replay configuration file.
For each host that is to be included in the recording session, call pmRecordAddHost. A new pmRecordHost structure is returned via rhp. It is assumed that PMCD is running on the host as this is how pmlogger retrieves the required performance metrics. See Section 3.8.8.1, “pmRecordAddHost Function” for more information.
Optionally, add arguments to the command line that is used to launch pmlogger by calling pmRecordControl with a request of PM_REC_SETARG. The argument is passed via options and one call to pmRecordControl is required for each distinct argument. See Section 3.8.8.2, “pmRecordControl Function” for more information.
To commence the recording session, call pmRecordControl with a request of PM_REC_ON, and rhp must be NULL.
To terminate a pmlogger instance identified by rhp, call pmRecordControl with a request of PM_REC_OFF.
To display the current status of the pmlogger instance identified by rhp, call pmRecordControl with a request of PM_REC_STATUS.
To detach a pmlogger instance identified by rhp, allow it to continue independent of the application that launched the recording session, call pmRecordControl with a request of PM_REC_DETACH.
The calling application should not close any of the returned stdio streams; pmRecordControl performs this task when recording is commenced.
Once pmlogger has been started for a recording session, pmlogger assumes responsibility for any dialogue with the user in the event that the application that launched the recording session should exit, particularly without terminating the recording session.
By default, information and dialogues from pmlogger is displayed using pmconfirm. This default is based on the assumption that most applications launching a recording session are GUI-based. In the event that pmconfirm fails to display the information (for example, because the DISPLAY environment variable is not set), pmlogger writes on its own stderr stream (not the stderr stream of the launching process). The output is assigned to the xxxxxx.host.log file. For convenience, the full pathname to this file is provided via the logfile field in the pmRecordHost structure.
If the options argument to pmRecordControl is not NULL, this string may be used to pass additional arguments to pmconfirm in those cases where a dialogue is to be displayed. One use of this capability is to provide a -geometry string to control the placement of the dialogue.
Premature termination of a launched pmlogger process may be determined using the pmRecordHost structure, by calling select on the fd_ipc field or polling the status field that will contain the termination status from waitpid if known, or -1.
These functions create a number of files in the same directory as the folio file named in the call to pmRecordSetup. In all cases, the xxxxxx component is the result of calling mkstemp.
If replay is nonzero, xxxxxx is the creator’s replay configuration file, else an empty control file, used to guarantee uniqueness.
The folio file is the PCP Archive Folio, suitable for use with the pmafm command.
The xxxxxx.host.config file is the pmlogger configuration for each host. If the same host is used in different calls to pmRecordAddHost within the same recording session, one of the letters ‘a’ through ‘z’ is appended to the xxxxxx part of all associated file names to ensure uniqueness.
xxxxxx.host.log is stdout and stderr for the pmlogger instance for each host.
The xxxxxx.host.{0,meta,index} files comprise a single PCP archive for each host.
pmRecordSetup may return NULL in the event of an error. Check errno for the real cause. The value EINVAL typically means that the order of calls to these functions is not correct; that is, there is an obvious state associated with the current recording session that is maintained across calls to the functions.
For example, calling pmRecordControl before calling pmRecordAddHost at least once, or calling pmRecordAddHost before calling pmRecordSetup would produce an EINVAL error.
3.8.9. PMAPI Archive-Specific Services¶
The functions described in this section provide archive-specific services.
3.8.9.1. pmGetArchiveLabel Function¶
int pmGetArchiveLabel(pmLogLabel *lp)
Python:
pmLogLabel loglabel = pmGetArchiveLabel()
Provided the current PMAPI context is associated with a set of PCP archive logs, the pmGetArchiveLabel function may be used to fetch the label record from the first archive in the set of archives. The structure returned through lp is as shown in Example 3.17. pmLogLabel Structure:
Example 3.17. pmLogLabel Structure
/*
* Label Record at the start of every log file - as exported above the PMAPI ...
*/
#define PM_TZ_MAXLEN 40
#define PM_LOG_MAXHOSTLEN 64
#define PM_LOG_MAGIC 0x50052600
#define PM_LOG_VERS01 0x1
#define PM_LOG_VERS02 0x2
#define PM_LOG_VOL_TI -2 /* temporal index */
#define PM_LOG_VOL_META -1 /* meta data */
typedef struct {
int ll_magic; /* PM_LOG_MAGIC | log format version no. */
pid_t ll_pid; /* PID of logger */
struct timeval ll_start; /* start of this log */
char ll_hostname[PM_LOG_MAXHOSTLEN]; /* name of collection host */
char ll_tz[PM_TZ_MAXLEN]; /* $TZ at collection host */
} pmLogLabel;
The python bindings get the label record from the archive.
3.8.9.2. pmGetArchiveEnd Function¶
int pmGetArchiveEnd(struct timeval *tvp)
Python:
timeval tv = status = pmGetArchiveEnd()
Provided the current PMAPI context is associated with a set of PCP archive logs, pmGetArchiveEnd finds the logical end of the last archive file in the set (after the last complete record in the archive), and returns the last recorded time stamp with tvp. This timestamp may be passed to pmSetMode to reliably position the context at the last valid log record, for example, in preparation for subsequent reading in reverse chronological order.
For archive logs that are not concurrently being written, the physical end of file and the logical end of file are co-incident. However, if an archive log is being written by pmlogger at the same time that an application is trying to read the archive, the logical end of file may be before the physical end of file due to write buffering that is not aligned with the logical record boundaries.
The python bindings get the last recorded timestamp from the archive.
3.8.9.3. pmGetInDomArchive Function¶
int pmGetInDomArchive(pmInDom indom, int **instlist, char ***namelist )
Python:
((instance1, instance2...) (name1, name2...)) pmGetInDom(pmDesc pmdesc)
Provided the current PMAPI context is associated with a set of PCP archive logs, pmGetInDomArchive scans the metadata to generate the union of all instances for the instance domain indom that can be found in the set of archive logs, and returns through instlist the internal instance identifiers, and through namelist the full external identifiers.
This function is a specialized version of the more general PMAPI function pmGetInDom.
The function returns the number of instances found (a value less than zero indicates an error).
The resulting lists of instance identifiers (instlist and namelist), and the names that the elements of namelist point to, are allocated by pmGetInDomArchive with two calls to malloc, and it is the responsibility of the caller to use free**(*instlist*) and **free**(*namelist*) to release the space when it is no longer required; see the **malloc(3) and free(3) man pages.
When the result of pmGetInDomArchive is less than one, both instlist and namelist are undefined (no space is allocated; so calling free is a singularly bad idea).
The python bindings return a tuple of the instance IDs and names for the union of all instances for the instance domain pmdesc that can be found in the archive log.
3.8.9.4. pmLookupInDomArchive Function¶
int pmLookupInDomArchive(pmInDom indom, const char *name)
Python:
c_uint instid = pmLookupInDomArchive(pmDesc pmdesc, "Instance")
Provided the current PMAPI context is associated with a set of PCP archive logs, pmLookupInDomArchive scans the metadata for the instance domain indom, locates the first instance with the external identification given by name, and returns the internal instance identifier.
This function is a specialized version of the more general PMAPI function pmLookupInDom.
The pmLookupInDomArchive function returns a positive instance identifier on success.
The python bindings return the instance id in pmdesc corresponding to Instance.
3.8.9.5. pmNameInDomArchive Function¶
int pmNameInDomArchive(pmInDom indom, int inst, char **name)
Python:
"instance id" = pmNameInDomArchive(pmDesc pmdesc, c_uint instid)
Provided the current PMAPI context is associated with a set of PCP archive logs, pmNameInDomArchive scans the metadata for the instance domain indom, locates the first instance with the internal instance identifier given by inst, and returns the full external instance identification through name. This function is a specialized version of the more general PMAPI function pmNameInDom.
The space for the value of name is allocated in pmNameInDomArchive with malloc, and it is the responsibility of the caller to free the space when it is no longer required; see the malloc(3) and free(3) man pages.
The python bindings return the text name of an instance corresponding to an instance domain pmdesc with instance identifier instid.
3.8.9.6. pmFetchArchive Function¶
int pmFetchArchive(pmResult **result)
Python:
pmResult* pmresult = pmFetchArchive()
This is a variant of pmFetch that may be used only when the current PMAPI context is associated with a set of PCP archive logs. The result is instantiated with all of the metrics (and instances) from the next archive record; consequently, there is no notion of a list of desired metrics, and the instance profile is ignored.
It is expected that pmFetchArchive would be used to create utilities that scan archive logs (for example, pmdumplog and pmlogsummary), and the more common access to the archives would be through the pmFetch interface.
3.8.10. PMAPI Time Control Services¶
The PMAPI provides a common framework for client applications to control time and to synchronize time with other applications. The user interface component of this service is fully described in the companion Performance Co-Pilot User’s and Administrator’s Guide. See also the pmtime(1) man page.
This service is most useful when processing sets of PCP archive logs, to control parameters such as the current archive position, update interval, replay rate, and timezone, but it can also be used in live mode to control a subset of these parameters. Applications such as pmchart, pmgadgets, pmstat, and pmval use the time control services to connect to an instance of the time control server process, pmtime, which provides a uniform graphical user interface to the time control services.
A full description of the PMAPI time control functions along with code examples can be found in man pages as listed in Table 3.2. Time Control Functions in PMAPI:
Table 3.2. Time Control Functions in PMAPI
Man Page |
Synopsis of Time Control Function |
pmCtime(3) |
Formats the date and time for a reporting timezone. |
pmLocaltime(3) |
Converts the date and time for a reporting timezone. |
pmParseTimeWindow(3) |
Parses time window command line arguments. |
pmTimeConnect(3) |
Connects to a time control server via a command socket. |
pmTimeDisconnect(3) |
Closes the command socket to the time control server. |
pmTimeGetPort(3) |
Obtains the port name of the current time control server. |
pmTimeRecv(3) |
Blocks until the time control server sends a command message. |
pmTimeSendAck(3) |
Acknowledges completion of the step command. |
pmTimeSendBounds(3) |
Specifies beginning and end of archive time period. |
pmTimeSendMode(3) |
Requests time control server to change to a new VCR mode. |
pmTimeSendPosition(3) |
Requests time control server to change position or update intervals. |
pmTimeSendTimezone(3) |
Requests time control server to change timezones. |
pmTimeShowDialog(3) |
Changes the visibility of the time control dialogue. |
pmTimeGetStatePixmap(3) |
Returns array of pixmaps representing supplied time control state. |
3.8.11. PMAPI Ancillary Support Services¶
The functions described in this section provide services that are complementary to, but not necessarily a part of, the distributed manipulation of performance metrics delivered by the PCP components.
3.8.11.1. pmGetConfig Function¶
char *pmGetConfig(const char *variable)
Python:
"env variable value = pmGetConfig("env variable")
The pmGetConfig function searches for a variable first in the environment and then, if one is not found, in the PCP configuration file and returns the string result. If a variable is not already in the environment, it is added with a call to the setenv function before returning.
The default location of the PCP configuration file is /etc/pcp.conf, but this location may be changed by setting PCP_CONF in the environment to a new location, as described in the pcp.conf(5) man page.
If the variable is not found in either the environment or the PCP configuration file (or the PCP configuration file is not found and PCP_CONF is not set in the environment), then a fatal error message is printed and the process will exit. Although this sounds drastic, it is the only course of action available because the PCP configuration or installation is fatally flawed.
If this function returns, the returned value points to a string in the environment; and so although the function returns the same type as the getenv function (which should probably be a const char *), changing the content of the string is not recommended.
The python bindings return a value for environment variable “env variable” from environment or pcp config file.
3.8.11.2. pmErrStr Function¶
const char *pmErrStr(int code)
char *pmErrStr_r(int code, char *buf, int buflen);
Python:
"error string text" = pmErrStr(int error_code)
This function translates an error code into a text string, suitable for generating a diagnostic message. By convention within PCP, all error codes are negative. The small values are assumed to be negated versions of the platform error codes as defined in errno.h, and the strings returned are according to strerror. The large, negative error codes are PMAPI error conditions, and pmErrStr returns an appropriate PMAPI error string, as determined by code.
In the case of pmErrStr, the string value is held in a single static buffer, so concurrent calls may not produce the desired results. The pmErrStr_r function allows a buffer and length to be passed in, into which the message is stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings return the error string corresponding to the error code.
3.8.11.3. pmExtractValue Function¶
int pmExtractValue(int valfmt, const pmValue *ival, int itype,
pmAtomValue *oval, int otype)
Python:
pmAtomValue atomval = pmExtractValue(int valfmt, const pmValue * ival,
int itype,
pmAtomValue *oval,
int otype)
The pmValue structure is embedded within the pmResult structure, which is used to return one or more performance metrics; see the pmFetch man page.
All performance metric values may be encoded in a pmAtomValue union, defined in Example 3.18. pmAtomValue Structure:
Example 3.18. pmAtomValue Structure
/* Generic Union for Value-Type conversions */
typedef union {
__int32_t l; /* 32-bit signed */
__uint32_t ul; /* 32-bit unsigned */
__int64_t ll; /* 64-bit signed */
__uint64_t ull; /* 64-bit unsigned */
float f; /* 32-bit floating point */
double d; /* 64-bit floating point */
char *cp; /* char ptr */
void *vp; /* void ptr */
} pmAtomValue;
The pmExtractValue function provides a convenient mechanism for extracting values from the pmValue part of a pmResult structure, optionally converting the data type, and making the result available to the application programmer.
The itype argument defines the data type of the input value held in ival according to the storage format defined by valfmt (see the pmFetch man page). The otype argument defines the data type of the result to be placed in oval. The value for itype is typically extracted from a pmDesc structure, following a call to pmLookupDesc for a particular performance metric.
Table 3.3. PMAPI Type Conversion defines the various possibilities for the type conversion. The input type (itype) is shown vertically, and the output type (otype) horizontally. The following rules apply:
Y means the conversion is always acceptable.
N means conversion can never be performed (function returns PM_ERR_CONV).
P means the conversion may lose accuracy (but no error status is returned).
T means the result may be subject to high-order truncation (if this occurs the function returns PM_ERR_TRUNC).
S means the conversion may be impossible due to the sign of the input value (if this occurs the function returns PM_ERR_SIGN).
If an error occurs, oval is set to zero (or NULL).
Note
Note that some of the conversions involving the PM_TYPE_STRING and PM_TYPE_AGGREGATE types are indeed possible, but are marked N; the rationale is that pmExtractValue should not attempt to duplicate functionality already available in the C library through sscanf and sprintf. No conversion involving the type PM_TYPE_EVENT is supported.
Table 3.3. PMAPI Type Conversion
TYPE |
32 |
U32 |
64 |
U64 |
FLOAT |
DBLE |
STRING |
AGGR |
EVENT |
|---|---|---|---|---|---|---|---|---|---|
32 |
Y |
S |
Y |
S |
P |
P |
N |
N |
N |
U32 |
T |
Y |
Y |
Y |
P |
P |
N |
N |
N |
64 |
T |
T,S |
Y |
S |
P |
P |
N |
N |
N |
u64 |
T |
T |
T |
Y |
P |
P |
N |
N |
N |
FLOAT |
P,T |
P,T,S |
P,T |
P,T,S |
Y |
Y |
N |
N |
N |
DBLE |
P,T |
P,T,S |
P,T |
P,T,S |
P |
Y |
N |
N |
N |
STRING |
N |
N |
N |
N |
N |
N |
Y |
N |
N |
AGGR |
N |
N |
N |
N |
N |
N |
N |
Y |
N |
EVENT |
N |
N |
N |
N |
N |
N |
N |
N |
N |
In the cases where multiple conversion errors could occur, the first encountered error is returned, and the order of checking is not defined.
If the output conversion is to one of the pointer types, such as otype PM_TYPE_STRING or PM_TYPE_AGGREGATE, then the value buffer is allocated by pmExtractValue using malloc, and it is the caller’s responsibility to free the space when it is no longer required; see the malloc(3) and free(3) man pages.
Although this function appears rather complex, it has been constructed to assist the development of performance tools that convert values, whose type is known only through the type field in a pmDesc structure, into a canonical type for local processing.
The python bindings extract a value from a pmValue struct ival stored in format valfmt (see pmFetch), and convert its type from itype to otype.
3.8.11.4. pmConvScale Function¶
int
pmConvScale(int type, const pmAtomValue *ival, const pmUnits *iunit,
pmAtomValue *oval, pmUnits *ounit)
Python:
pmAtomValue atomval = pmConvScale(int itype, pmAtomValue value,
pmDesc* pmdesc , int descidx, int otype)
Given a performance metric value pointed to by ival, multiply it by a scale factor and return the value in oval. The scaling takes place from the units defined by iunit into the units defined by ounit. Both input and output units must have the same dimensionality.
The performance metric type for both input and output values is determined by type, the value for which is typically extracted from a pmDesc structure, following a call to pmLookupDesc for a particular performance metric.
pmConvScale is most useful when values returned through pmFetch (and possibly extracted using pmExtractValue) need to be normalized into some canonical scale and units for the purposes of computation.
The python bindings convert a value pointed to by pmdesc entry descidx to a different scale otype.
3.8.11.5. pmUnitsStr Function¶
const char *pmUnitsStr(const pmUnits *pu)
char *pmUnitsStr_r(const pmUnits *pu, char *buf, int buflen)
Python:
"units string" = pmUnitsStr(pmUnits pmunits)
As an aid to labeling graphs and tables, or for error messages, pmUnitsStr takes a dimension and scale specification as per pu, and returns the corresponding text string.
pu is typically from a pmDesc structure, for example, as returned by pmLookupDesc.
If *pu were {1, -2, 0, PM_SPACE_MBYTE, PM_TIME_MSEC, 0}, then the result string would be Mbyte/sec^2.
In the case of pmUnitsStr, the string value is held in a single static buffer; so concurrent calls may not produce the desired results. The pmUnitsStr_r function allows a buffer and length to be passed in, into which the units are stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings translate a pmUnits struct pmunits to a readable string.
3.8.11.6. pmIDStr Function¶
const char *pmIDStr(pmID pmid)
char *pmIDStr_r(pmID pmid, char *buf, int buflen)
Python:
"ID string" = pmIDStr(int pmID)
For use in error and diagnostic messages, return a human readable version of the specified PMID, with each of the internal domain, cluster, and item subfields appearing as decimal numbers, separated by periods.
In the case of pmIDStr, the string value is held in a single static buffer; so concurrent calls may not produce the desired results. The pmIDStr_r function allows a buffer and length to be passed in, into which the identifier is stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings translate a pmID pmid to a readable string.
3.8.11.7. pmInDomStr Function¶
const char *pmInDomStr(pmInDom indom)
char *pmInDomStr_r(pmInDom indom, char *buf, int buflen)
Python:
"indom" = pmGetInDom(pmDesc pmdesc)
For use in error and diagnostic messages, return a human readable version of the specified instance domain identifier, with each of the internal domain and serial subfields appearing as decimal numbers, separated by periods.
In the case of pmInDomStrr, the string value is held in a single static buffer; so concurrent calls may not produce the desired results. The pmInDomStr_r function allows a buffer and length to be passed in, into which the identifier is stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings translate an instance domain ID pointed to by a pmDesc pmdesc to a readable string.
3.8.11.8. pmTypeStr Function¶
const char *pmTypeStr(int type)
char *pmTypeStr_r(int type, char *buf, int buflen)
Python:
"type" = pmTypeStr(int type)
Given a performance metric type, produce a terse ASCII equivalent, appropriate for use in error and diagnostic messages.
Examples are “32” (for PM_TYPE_32), “U64” (for PM_TYPE_U64), “AGGREGATE” (for PM_TYPE_AGGREGATE), and so on.
In the case of pmTypeStr, the string value is held in a single static buffer; so concurrent calls may not produce the desired results. The pmTypeStr_r function allows a buffer and length to be passed in, into which the identifier is stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings translate a performance metric type to a readable string. Constants are available for the types, e.g. c_api.PM_TYPE_FLOAT, by importing cpmapi.
3.8.11.9. pmAtomStr Function¶
const char *pmAtomStr(const pmAtomValue *avp, int type)
char *pmAtomStr_r(const pmAtomValue *avp, int typechar *buf, int buflen)
Python:
"value" = pmAtomStr(atom, type)
Given the pmAtomValue identified by avp, and a performance metric type, generate the corresponding metric value as a string, suitable for diagnostic or report output.
In the case of pmAtomStr, the string value is held in a single static buffer; so concurrent calls may not produce the desired results. The pmAtomStr_r function allows a buffer and length to be passed in, into which the identifier is stored; this variant uses no shared storage and can be used in a thread-safe manner.
The python bindings translate a pmAtomValue atom having performance metric type to a readable string. Constants are available for the types, e.g. c_api.PM_TYPE_U32, by importing cpmapi.
3.8.11.10. pmNumberStr Function¶
const char *pmNumberStr(double value)
char *pmNumberStr_r(double value, char *buf, int buflen)
The pmNumberStr function returns the address of a static 8-byte buffer that holds a null-byte terminated representation of value suitable for output with fixed-width fields.
The value is scaled using multipliers in powers of one thousand (the decimal kilo) and has a bias that provides greater precision for positive numbers as opposed to negative numbers. The format depends on the sign and magnitude of value.
3.8.11.11. pmPrintValue Function¶
void pmPrintValue(FILE *f, int valfmt, int type, const pmValue *val,
int minwidth)
Python:
pmPrintValue(FILE* file, pmResult pmresult, pmdesc, vset_index, vlist_index, min_width)
The value of a single performance metric (as identified by val) is printed on the standard I/O stream identified by f. The value of the performance metric is interpreted according to the format of val as defined by valfmt (from a pmValueSet within a pmResult) and the generic description of the metric’s type from a pmDesc structure, passed in through.
If the converted value is less than minwidth characters wide, it will have leading spaces to pad the output to a width of minwidth characters.
Example 3.19. Using pmPrintValue to Print Values illustrates using pmPrintValue to print the values from a pmResult structure returned via pmFetch:
Example 3.19. Using pmPrintValue to Print Values
int numpmid, i, j, sts;
pmID pmidlist[10];
pmDesc desc[10];
pmResult *result;
/* set up PMAPI context, numpmid and pmidlist[] ... */
/* get metric descriptors */
for (i = 0; i < numpmid; i++) {
if ((sts = pmLookupDesc(pmidlist[i], &desc[i])) < 0) {
printf("pmLookupDesc(pmid=%s): %s\n",
pmIDStr(pmidlist[i]), pmErrStr(sts));
exit(1);
}
}
if ((sts = pmFetch(numpmid, pmidlist, &result)) >= 0) {
/* once per metric */
for (i = 0; i < result->numpmid; i++) {
printf("PMID: %s", pmIDStr(result->vset[i]->pmid));
/* once per instance for this metric */
for (j = 0; j < result->vset[i]->numval; j++) {
printf(" [%d]", result->vset[i]->vlist[j].inst);
pmPrintValue(stdout, result->vset[i]->valfmt,
desc[i].type,
&result->vset[i]->vlist[j],
8);
}
putchar('\n');
}
pmFreeResult(result);
}
else
printf("pmFetch: %s\n", pmErrStr(sts));
Print the value of a pmresult pointed to by vset_index/vlist_index and described by pmdesc. The format of a pmResult is described in pmResult The python bindings can use sys.__stdout__ as a value for file to display to stdout.
3.8.11.12. pmflush Function¶
int pmflush(void);
Python:
int status = pmflush()
The pmflush function causes the internal buffer which is shared with pmprintf to be either displayed in a window, printed on standard error, or flushed to a file and the internal buffer to be cleared.
The PCP_STDERR environment variable controls the output technique used by pmflush:
If PCP_STDERR is unset, the text is written onto the stderr stream of the caller.
If PCP_STDERR is set to the literal reserved word DISPLAY, then the text is displayed as a GUI dialogue using pmconfirm.
The pmflush function returns a value of zero on successful completion. A negative value is returned if an error was encountered, and this can be passed to pmErrStr to obtain the associated error message.
3.8.11.13. pmprintf Function¶
int pmprintf(const char *fmt, ... /*args*/);
Python:
pmprintf("fmt", ... /*args*/);
The pmprintf function appends the formatted message string to an internal buffer shared by the pmprintf and pmflush functions, without actually producing any output. The fmt argument is used to control the conversion, formatting, and printing of the variable length args list.
The pmprintf function uses the mkstemp function to securely create a pcp-prefixed temporary file in ${PCP_TMP_DIR}. This temporary file is deleted
when pmflush is called.
On successful completion, pmprintf returns the number of characters transmitted. A negative value is returned if an error was encountered, and this can be passed to pmErrStr to obtain the associated error message.
3.8.11.14. pmSortInstances Function¶
void pmSortInstances(pmResult *result)
Python:
pmSortInstances (pmResult* pmresult)
The pmSortInstances function may be used to guarantee that for each performance metric in the result from pmFetch, the instances are in ascending internal instance identifier sequence. This is useful when trying to compute rates from two consecutive pmFetch results, where the underlying instance domain or metric availability is not static.
3.8.11.15. pmParseInterval Function¶
int pmParseInterval(const char *string, struct timeval *rslt, char **errmsg)
Python:
(struct timeval, "error message") = pmParseInterval("time string")
The pmParseInterval function parses the argument string specifying an interval of time and fills in the tv_sec and tv_usec components of the rslt structure to represent that interval. The input string is most commonly the argument following a -t command line option to a PCP application, and the syntax is fully described in the PCPIntro(1) man page.
pmParseInterval returns 0 and errmsg is undefined if the parsing is successful. If the given string does not conform to the required syntax, the function returns -1 and a dynamically allocated error message string in errmsg.
The error message is terminated with a newline and includes the text of the input string along with an indicator of the position at which the error was detected as shown in the following example:
4minutes 30mumble
^ -- unexpected value
In the case of an error, the caller is responsible for calling free to release the space allocated for errmsg.
3.8.11.16. pmParseMetricSpec Function¶
int pmParseMetricSpec(const char *string, int isarch, char *source,
pmMetricSpec **rsltp, char **errmsg)
Python:
(pmMetricSpec metricspec, "error message") =
pmParseMetricSpec("metric specification", isarch, source)
The pmParseMetricSpec function accepts a string specifying the name of a PCP performance metric, and optionally the source (either a hostname, a set of PCP archive logs, or a local context) and instances for that metric. The syntax is described in the PCPIntro(1) man page.
If neither host nor archive component of the metric specification is provided, the isarch and source arguments are used to fill in the returned pmMetricSpec structure. In Example 3.20. pmMetricSpec Structure, the pmMetricSpec structure, which is returned via rsltp, represents the parsed string.
Example 3.20. pmMetricSpec Structure
typedef struct {
int isarch; /* source type: 0 -> host, 1 -> archive, 2 -> local context */
char *source; /* name of source host or archive */
char *metric; /* name of metric */
int ninst; /* number of instances, 0 -> all */
char *inst[1]; /* array of instance names */
} pmMetricSpec;
The pmParseMetricSpec function returns 0 if the given string was successfully parsed. In this case, all the storage allocated by pmParseMetricSpec can be released by a single call to the free function by using the address returned from pmMetricSpec via rsltp. The convenience macro pmFreeMetricSpec is a thinly disguised wrapper for free.
The pmParseMetricSpec function returns 0 if the given string was successfully parsed. It returns PM_ERR_GENERIC and a dynamically allocated error message string in errmsg if the given string does not parse. In this situation, the error message string can be released with the free function.
In the case of an error, rsltp is undefined. In the case of success, errmsg is undefined. If rsltp->ninst is 0, then rsltp->inst[0] is undefined.
3.9. PMAPI Programming Issues and Examples¶
The following issues and examples are provided to enable you to create better custom performance monitoring tools.
The source code for a sample client (pmclient) using the PMAPI is shipped as part of the PCP package. See the pmclient(1) man page, and the source code,
located in ${PCP_DEMOS_DIR}/pmclient.
3.9.1. Symbolic Association between a Metric’s Name and Value¶
A common problem in building specific performance tools is how to maintain the association between a performance metric’s name, its access (instantiation) method, and the application program variable that contains the metric’s value. Generally this results in code that is easily broken by bug fixes or changes in the underlying data structures. The PMAPI provides a uniform method for instantiating and accessing the values independent of the underlying implementation, although it does not solve the name-variable association problem. However, it does provide a framework within which a manageable solution may be developed.
Fundamentally, the goal is to be able to name a metric and reference the metric’s value in a manner that is independent of the order of operations on other metrics; for example, to associate the LOADAV macro with the name kernel.all.load, and then be able to use LOADAV to get at the value of the corresponding metric.
The one-to-one association between the ordinal position of the metric names is input to pmLookupName and the PMIDs returned by this function, and the one-to-one association between the PMIDs input to pmFetch and the values returned by this function provide the basis for an automated solution.
The tool pmgenmap takes the specification of a list of metric names and symbolic tags, in the order they should be passed to pmLookupName and pmFetch. For example, pmclient:
cat ${PCP_DEMOS_DIR}/pmclient/pmnsmap.spec
pmclient_init {
hinv.ncpu NUMCPU
}
pmclient_sample {
kernel.all.load LOADAV
kernel.percpu.cpu.user CPU_USR
kernel.percpu.cpu.sys CPU_SYS
mem.freemem FREEMEM
disk.all.total DKIOPS
}
This pmgenmap input produces the C code in Example 3.21. C Code Produced by pmgenmap Input. It is suitable for including with the #include statement:
Example 3.21. C Code Produced by pmgenmap Input
/*
* Performance Metrics Name Space Map
* Built by runme.sh from the file
* pmnsmap.spec
* on Thu Jan 9 14:13:49 EST 2014
*
* Do not edit this file!
*/
char *pmclient_init[] = {
#define NUMCPU 0
"hinv.ncpu",
};
char *pmclient_sample[] = {
#define LOADAV 0
"kernel.all.load",
#define CPU_USR 1
"kernel.percpu.cpu.user",
#define CPU_SYS 2
"kernel.percpu.cpu.sys",
#define FREEMEM 3
"mem.freemem",
#define DKIOPS 4
"disk.all.total",
};
3.9.2. Initializing New Metrics¶
Using the code generated by pmgenmap, you are now able to easily initialize the application’s metric specifications as shown in Example 3.22. Initializing Metric Specifications:
Example 3.22. Initializing Metric Specifications
/* C code fragment from pmclient.c */
numpmid = sizeof(pmclient_sample) / sizeof(char *);
if ((pmidlist = (pmID *)malloc(numpmid * sizeof(pmidlist[0]))) == NULL) {...}
if ((sts = pmLookupName(numpmid, pmclient_sample, pmidlist)) < 0) {...}
# The equivalent python code would be
pmclient_sample = ("kernel.all.load", "kernel.percpu.cpu.user",
"kernel.percpu.cpu.sys", "mem.freemem", "disk.all.total")
pmidlist = context.pmLookupName(pmclient_sample)
At this stage, pmidlist contains the PMID for the five metrics of interest.
3.9.3. Iterative Processing of Values¶
Assuming the tool is required to report values every delta seconds, use code similar to that in Example 3.23. Iterative Processing:
Example 3.23. Iterative Processing
/* censored C code fragment from pmclient.c */
while (samples == -1 || samples-- > 0) {
if ((sts = pmFetch(numpmid, pmidlist, &crp)) < 0) { ... }
for (i = 0; i < numpmid; i++)
if ((sts = pmLookupDesc(pmidlist[i], &desclist[i])) < 0) { ... }
...
pmExtractValue(crp->vset[FREEMEM]->valfmt, crp->vset[FREEMEM]->vlist,
desclist[FREEMEM].type, &tmp, PM_TYPE_FLOAT);
pmConvScale(PM_TYPE_FLOAT, &tmp, &desclist[FREEMEM].units,
&atom, &mbyte_scale);
ip->freemem = atom.f;
...
__pmtimevalSleep(delta);
}
# The equivalent python code would be
FREEMEM = 3
desclist = context.pmLookupDescs(metric_names)
while (samples > 0):
crp = context.pmFetch(metric_names)
val = context.pmExtractValue(crp.contents.get_valfmt(FREEMEM),
crp.contents.get_vlist(FREEMEM, 0),
desclist[FREEMEM].contents.type,
c_api.PM_TYPE_FLOAT)
atom = ctx.pmConvScale(c_api.PM_TYPE_FLOAT, val, desclist, FREEMEM,
c_api.PM_SPACE_MBYTE)
(tvdelta, errmsg) = c_api.pmParseInterval(delta)
c_api.pmtimevalSleep(delta)
3.9.4. Accommodating Program Evolution¶
The flexibility provided by the PMAPI and the pmgenmap utility is demonstrated by Example 3.24. Adding a Metric. Consider the requirement for reporting a third metric mem.physmem. This example shows how to add the line to the specification file:
Example 3.24. Adding a Metric
mem.freemem PHYSMEM
Then regenerate the #include file, and augment pmclient.c:
pmExtractValue(crp->vset[PHYSMEM]->valfmt, crp->vset[PHYSMEM]->vlist,
desclist[PHYSMEM].type, &tmp, PM_TYPE_FLOAT);
pmConvScale(PM_TYPE_FLOAT, &tmp, &desclist[PHYSMEM].units,
&atom, &mbyte_scale);
# The equivalent python code would be:
val = context.pmExtractValue(crp.contents.get_valfmt(PHYSMEM),
crp.contents.get_vlist(PHYSMEM, 0),
desclist[PHYSMEM].contents.type,
c_api.PM_TYPE_FLOAT);
3.9.5. Handling PMAPI Errors¶
In Example 3.25. PMAPI Error Handling, the simple but complete PMAPI application demonstrates the recommended style for handling PMAPI error conditions. The python bindings use the exception mechanism to raise an exception in error cases. The python client can handle this condition by catching the pmErr exception. For simplicity, no command line argument processing is shown here - in practice most tools use the pmGetOptions helper interface to assist with initial context creation and setup.
Example 3.25. PMAPI Error Handling
#include <pcp/pmapi.h>
int
main(int argc, char* argv[])
{
int sts = 0;
char *host = "local:";
char *metric = "mem.freemem";
pmID pmid;
pmDesc desc;
pmResult *result;
sts = pmNewContext(PM_CONTEXT_HOST, host);
if (sts < 0) {
fprintf(stderr, "Error connecting to pmcd on %s: %s\n",
host, pmErrStr(sts));
exit(1);
}
sts = pmLookupName(1, &metric, &pmid);
if (sts < 0) {
fprintf(stderr, "Error looking up %s: %s\n", metric,
pmErrStr(sts));
exit(1);
}
sts = pmLookupDesc(pmid, &desc);
if (sts < 0) {
fprintf(stderr, "Error getting descriptor for %s:%s: %s\n",
host, metric, pmErrStr(sts));
exit(1);
}
sts = pmFetch(1, &pmid, &result);
if (sts < 0) {
fprintf(stderr, "Error fetching %s:%s: %s\n", host, metric,
pmErrStr(sts));
exit(1);
}
sts = result->vset[0]->numval;
if (sts < 0) {
fprintf(stderr, "Error fetching %s:%s: %s\n", host, metric,
pmErrStr(sts));
exit(1);
}
fprintf(stdout, "%s:%s = ", host, metric);
if (sts == 0)
puts("(no value)");
else {
pmValueSet *vsp = result->vset[0];
pmPrintValue(stdout, vsp->valfmt, desc.type,
&vsp->vlist[0], 5);
printf(" %s\n", pmUnitsStr(&desc.units));
}
return 0;
}
The equivalent python code would be:
import sys
import traceback
from pcp import pmapi
from cpmapi import PM_TYPE_U32
try:
context = pmapi.pmContext()
pmid = context.pmLookupName("mem.freemem")
desc = context.pmLookupDescs(pmid)
result = context.pmFetch(pmid)
freemem = context.pmExtractValue(result.contents.get_valfmt(0),
result.contents.get_vlist(0, 0),
desc[0].contents.type,
PM_TYPE_U32)
print "freemem is " + str(int(freemem.ul))
except pmapi.pmErr, error:
print "%s: %s" % (sys.argv[0], error.message())
except Exception, error:
sys.stderr.write(str(error) + "\n")
sys.stderr.write(traceback.format_exc() + "\n")
3.9.6. Compiling and Linking PMAPI Applications¶
Typical PMAPI applications require the following line to include the function prototype and data structure definitions used by the PMAPI.
#include <pcp/pmapi.h>
Some applications may also require these header files: <pcp/libpcp.h> and <pcp/pmda.h>.
The run-time environment of the PMAPI is mostly found in the libpcp library; so to link a generic PMAPI application requires something akin to the following command:
cc mycode.c -lpcp