--- /dev/null
+=================
+ Perf histograms
+=================
+
+The perf histograms build on perf counters infrastructure. Histograms are built for a number of counters and simplify gathering data on which groups of counter values occur most often over time.
+Perf histograms are currently unsigned 64-bit integer counters, so they're mostly useful for time and sizes. Data dumped by perf histogram can then be feed into other analysis tools/scripts.
+
+Access
+------
+
+The perf histogram data are accessed via the admin socket. For example::
+
+ ceph daemon osd.0 perf histogram schema
+ ceph daemon osd.0 perf histogram dump
+
+
+Collections
+-----------
+
+The histograms are grouped into named collections, normally representing a subsystem or an instance of a subsystem. For example, the internal ``throttle`` mechanism reports statistics on how it is throttling, and each instance is named something like::
+
+
+ op_r_latency_out_bytes_histogram
+ op_rw_latency_in_bytes_histogram
+ op_rw_latency_out_bytes_histogram
+ ...
+
+
+Schema
+------
+
+The ``perf histogram schema`` command dumps a json description of which values are available, and what their type is. Each named value as a ``type`` bitfield, with the 5-th bit always set and following bits defined.
+
++------+-------------------------------------+
+| bit | meaning |
++======+=====================================+
+| 1 | floating point value |
++------+-------------------------------------+
+| 2 | unsigned 64-bit integer value |
++------+-------------------------------------+
+| 4 | average (sum + count pair) |
++------+-------------------------------------+
+| 8 | counter (vs gauge) |
++------+-------------------------------------+
+
+In other words, histogram of type "18" is a histogram of unsigned 64-bit integer values (16 + 2).
+
+Here is an example of the schema output::
+
+ {
+ "AsyncMessenger::Worker-0": {},
+ "AsyncMessenger::Worker-1": {},
+ "AsyncMessenger::Worker-2": {},
+ "mutex-WBThrottle::lock": {},
+ "objecter": {},
+ "osd": {
+ "op_r_latency_out_bytes_histogram": {
+ "type": 18,
+ "description": "Histogram of operation latency (including queue time) + da ta read",
+ "nick": ""
+ },
+ "op_w_latency_in_bytes_histogram": {
+ "type": 18,
+ "description": "Histogram of operation latency (including queue time) + da ta written",
+ "nick": ""
+ },
+ "op_rw_latency_in_bytes_histogram": {
+ "type": 18,
+ "description": "Histogram of rw operation latency (including queue time) + data written",
+ "nick": ""
+ },
+ "op_rw_latency_out_bytes_histogram": {
+ "type": 18,
+ "description": "Histogram of rw operation latency (including queue time) + data read",
+ "nick": ""
+ }
+ }
+ }
+
+
+Dump
+----
+
+The actual dump is similar to the schema, except that there are actual value groups. For example::
+
+ "osd": {
+ "op_r_latency_out_bytes_histogram": {
+ "axes": [
+ {
+ "name": "Latency (usec)",
+ "min": 0,
+ "quant_size": 100000,
+ "buckets": 32,
+ "scale_type": "log2",
+ "ranges": [
+ {
+ "max": -1
+ },
+ {
+ "min": 0,
+ "max": 99999
+ },
+ {
+ "min": 100000,
+ "max": 199999
+ },
+ {
+ "min": 200000,
+ "max": 399999
+ },
+ {
+ "min": 400000,
+ "max": 799999
+ },
+ {
+ "min": 800000,
+ "max": 1599999
+ },
+ {
+ "min": 1600000,
+ "max": 3199999
+ },
+ {
+ "min": 3200000,
+ "max": 6399999
+ },
+ {
+ "min": 6400000,
+ "max": 12799999
+ },
+ {
+ "min": 12800000,
+ "max": 25599999
+ },
+ {
+ "min": 25600000,
+ "max": 51199999
+ },
+ {
+ "min": 51200000,
+ "max": 102399999
+ },
+ {
+ "min": 102400000,
+ "max": 204799999
+ },
+ {
+ "min": 204800000,
+ "max": 409599999
+ },
+ {
+ "min": 409600000,
+ "max": 819199999
+ },
+ {
+ "min": 819200000,
+ "max": 1638399999
+ },
+ {
+ "min": 1638400000,
+ "max": 3276799999
+ },
+ {
+ "min": 3276800000,
+ "max": 6553599999
+ },
+ {
+ "min": 6553600000,
+ "max": 13107199999
+ },
+ {
+ "min": 13107200000,
+ "max": 26214399999
+ },
+ {
+ "min": 26214400000,
+ "max": 52428799999
+ },
+ {
+ "min": 52428800000,
+ "max": 104857599999
+ },
+ {
+ "min": 104857600000,
+ "max": 209715199999
+ },
+ {
+ "min": 209715200000,
+ "max": 419430399999
+ },
+ {
+ "min": 419430400000,
+ "max": 838860799999
+ },
+ {
+ "min": 838860800000,
+ "max": 1677721599999
+ },
+ {
+ "min": 1677721600000,
+ "max": 3355443199999
+ },
+ {
+ "min": 3355443200000,
+ "max": 6710886399999
+ },
+ {
+ "min": 6710886400000,
+ "max": 13421772799999
+ },
+ {
+ "min": 13421772800000,
+ "max": 26843545599999
+ },
+ {
+ "min": 26843545600000,
+ "max": 53687091199999
+ },
+ },
+ {
+ "min": 53687091200000
+ }
+ ]
+ },
+ {
+ "name": "Request size (bytes)",
+ "min": 0,
+ "quant_size": 512,
+ "buckets": 32,
+ "scale_type": "log2",
+ "ranges": [
+ {
+ "max": -1
+ },
+ {
+ "min": 0,
+ "max": 511
+ },
+ {
+ "min": 512,
+ "max": 1023
+ },
+ {
+ "min": 1024,
+ "max": 2047
+ },
+ {
+ "min": 2048,
+ "max": 4095
+ },
+ {
+ "min": 4096,
+ "max": 8191
+ },
+ {
+ "min": 8192,
+ "max": 16383
+ },
+ {
+ "min": 16384,
+ "max": 32767
+ },
+ {
+ "min": 32768,
+ "max": 65535
+ },
+ {
+ "min": 65536,
+ "max": 131071
+ },
+ {
+ "min": 131072,
+ "max": 262143
+ },
+ {
+ "min": 262144,
+ "max": 524287
+ },
+ {
+ "min": 524288,
+ "max": 1048575
+ },
+ {
+ "min": 1048576,
+ "max": 2097151
+ },
+ {
+ "min": 2097152,
+ "max": 4194303
+ },
+ {
+ "min": 4194304,
+ "max": 8388607
+ },
+ {
+ "min": 8388608,
+ "max": 16777215
+ },
+ {
+ "min": 16777216,
+ "max": 33554431
+ },
+ {
+ "min": 33554432,
+ "max": 67108863
+ },
+ {
+ "min": 67108864,
+ "max": 134217727
+ },
+ {
+ "min": 134217728,
+ "max": 268435455
+ },
+ {
+ "min": 268435456,
+ "max": 536870911
+ },
+ {
+ "min": 536870912,
+ "max": 1073741823
+ },
+ {
+ "min": 1073741824,
+ "max": 2147483647
+ },
+ {
+ "min": 2147483648,
+ "max": 4294967295
+ },
+ {
+ "min": 4294967296,
+ "max": 8589934591
+ },
+ {
+ "min": 8589934592,
+ "max": 17179869183
+ },
+ {
+ "min": 17179869184,
+ "max": 34359738367
+ },
+ {
+ "min": 34359738368,
+ "max": 68719476735
+ },
+ {
+ "min": 68719476736,
+ "max": 137438953471
+ },
+ {
+ "min": 137438953472,
+ "max": 274877906943
+ },
+ {
+ "min": 274877906944
+ }
+ ]
+ }
+ ],
+ "values": [
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+ }
+ },
+
+This represents the 2d histogram, consisting of 9 history entrires and 32 value groups per each history entry.
+"Ranges" element denote value bounds for each of value groups. "Buckets" denote amount of value groups ("buckets"),
+"Min" is a minimum accepted valaue, "quant_size" is quantization unit and "scale_type" is either "log2" (logarhitmic
+scale) or "linear" (linear scale).
+You can use histogram_dump.py tool (see src/tools/histogram_dump.py) for quick visualisation of existing histogram
+data.
Code Review / stor4nfv.git / blobdiff