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4.4.3. Updating Mapped Values

At this stage we have individual handles (pointers) to each instrumentation point, we can now start modifying these values and observing changes through the PCP infrastructure. Notice that each handle is simply the canonical pmAtomValue pointer, as defined in Example 3.16, “ pmAtomValue Structure”, which is a union providing sufficient space to hold any single value.
This pointer can be either manipulated directly, or using helper functions provided by the pcp_mmv API, such as the mmv_stats_inc and mmv_stats_set functions.

Example 4.4. Memory Mapped Value Updates

    while (1) {
        /* choose a random number between 0-N -> product */
        product = rand() % ACME_PRODUCTS_COUNT;

        /* assign a time spent "working" on this product */
        working = rand() % 50000;

        /* pretend to "work" so process doesn't burn CPU */

        /* update the memory mapped values for this one: */
        /* one more product produced and work time spent */
        mmv_inc_value(base, machine[product], working); /* API */
        count[product]->ull += 1;     /* or direct mmap update */

        /* all other products are "queued" for this time */
        for (i = 0; i < ACME_PRODUCTS_COUNT; i++)
            if (i != product)
                mmv_inc_value(base, inqueue[i], working);
At this stage, it will be informative to compile and run the complete example program, which can be found in ${PCP_DEMOS_DIR}/mmv/acme.c. There is an associated Makefile to build it, in the same directory. Running the acme binary creates the instrumentation shown in Example 4.5, “Memory Mapped Value Reports”, with live values letting us explore simple queueing effects in products being created on the ACME factory floor.

Example 4.5. Memory Mapped Value Reports

              pminfo -m mmv.acme
mmv.acme.products.queuetime PMID: 70.321.10
mmv.acme.products.time PMID: 70.321.8
mmv.acme.products.count PMID: 70.321.7

pmval -f2 -s3 mmv.acme.products.time
metric:    mmv.acme.products.time
host:      localhost
semantics: cumulative counter (converting to rate)
units:     microsec (converting to time utilization)
samples:   3
interval:  1.00 sec

               Anvils               Rockets    Giant_Rubber_Bands 
                 0.37                  0.12                  0.50 
                 0.35                  0.25                  0.38 
                 0.57                  0.20                  0.23
Experimentation with the algorithm from Example 4.4, “Memory Mapped Value Updates” is encouraged. In particular, observe the effects of rate conversion (counter metric type) of a metric with units of "time" (PM_TIME_*). The reported values are calculated over a sampling interval, which also has units of "time", forming a utilization. This is extremely valuable performance analysis currency - comparable metrics would include processor utilization, disk spindle utilization, and so forth.