Buildbot/Talos/DataFormat

Talos Data

Raw data is generated by Talos. We apply some filters to summarize and reduce the data, then we post it to a server:

• Graphserver
• Perfherder

Terminology

Job

When a build is completed we run a series of test (unittest and performance "talos") jobs. Each job reserves a machine for itself, the runs the script which sets up, installs, executes the test, generates the results, and cleans up after itself.

For Talos we have a series of jobs and each job runs 1 or more tests. For the purposes of discussing data we will refer to each test as a suite. A suite would be something like 'ts_paint', 'Canvasmark', or 'tp5'. Each Suite will run it's respective subtests, and summarize itself properly. When all the suites in a job have completed, the results will be output (uploaded in some cases) and we will be able to look for regressions, view data in a graph, and query for the summarized data.

Suite

A collection of subtests which run, the subtest results are summarized to the suite level. Often these are referred to as 'tests'. Some examples are "tresize", "TART", "tp5", "ts_paint".

• in graph server this is the lowest level of granularity available in the UI
• in Perfherder a suite is referenced as a 'Summary' (e.g "tp5o summary opt")

Subtest

A specific test (usually a webpage to load) which we collect replicates (numbers) from. Typically we run many cycles of each subtest to build up a representative collection of replicates to make sure the data is meaningful.

• in graph server Talos upload a single number for each subtest, the replicates are summarized by Talos prior to uploading.
• in Perfherder the subtest data is preserved as raw replicates as well as summarized by Talos. We use the summarizations when showing a graph.

Replicates

Replicates mean the single numbers or data points we collect while executing a talos test. In this regard, we collect a series of numbers (usually 20 or more) for each subtest. Each of these 20+ numbers are called replicates.

We do filtering on the replicates, mainly because the first few replicates are not a representative sample of the remaining replicates we collect. The one exception would be internal benchmarks (generally suites which measure something other than time). For Benchmarks, there is usually a special formula applied to the replicates.

Perfherder

Perfherder ingests data from talos by parsing the raw log, then it stores the data in a database while preparing it for regression detection and displaying on graphs.

Raw Data

In the log files, we look for "TALOSDATA: " text followed by a valid json blob. An example TALOSDATA blob looks like:

 [{"talos_counters": {}, "results": {"tresize": [23.26174999999999, 22.99621666666672, 22.66563333333331, 23.99620000000002, 22.940849999999948, 22.26951666666664, 22.975350000000006, 24.96453333333337, 23.6878333333334, 23.21740000000001, 24.743699999999976, 23.507333333333282, 22.927800000000033, 22.292066666666653, 23.28364999999999, 23.361950000000004, 22.18191666666666, 22.996466666666684, 23.54029999999997, 22.873883333333342]}, "summary": {"suite": 23.21740000000001, "subtests": {"tresize": {"std": 0.7716690474213389, "min": 22.18191666666666, "max": 24.96453333333337, "median": 23.21740000000001, "filtered": 23.21740000000001, "mean": 23.254913333333334}}}, "test_machine": {"platform": "x86", "osversion": "Ubuntu 12.04", "os": "linux", "name": "talos-linux32-ix-040"}, "testrun": {"date": 1440091515, "suite": "tresize", "options": {"responsiveness": false, "cycles": 20, "tpmozafterpaint": true, "shutdown": false, "rss": false}}, "test_build": {"name": "Firefox", "version": "43.0a1", "id": "20150820095841", "branch": "Mozilla-Inbound-Non-PGO", "revision": "bb85ec539217b9d3a5e83c40538d8565d292e72b"}}, {"talos_counters": {}, "results": {"Plasma - Maths- canvas shapes": [545.0, 572.0, 598.0, 662.0, 588.0], "Asteroids - Shapes- shadows- blending": [748.0, 737.0, 720.0, 742.0, 743.0], "Asteroids - Bitmaps- shapes- text": [1031.0, 1011.0, 913.0, 1063.0, 888.0], "Arena5 - Vectors- shadows- bitmaps- text": [892.0, 738.0, 900.0, 920.0, 806.0], "Asteroids - Vectors": [675.0, 735.0, 659.0, 789.0, 768.0], "3D Rendering - Maths- polygons- image transforms": [306.0, 434.0, 388.0, 426.0, 389.0], "Pixel blur - Math- getImageData- putImageData": [1291.0, 1435.0, 1553.0, 1461.0, 1521.0], "Asteroids - Bitmaps": [435.0, 418.0, 410.0, 403.0, 380.0]}, "summary": {"suite": 6204.0, "subtests": {"Plasma - Maths- canvas shapes": {"std": 34.19064199455752, "min": 572.0, "max": 662.0, "median": 593.0, "filtered": 593.0, "mean": 605.0}, "Asteroids - Shapes- shadows- blending": {"std": 9.233092656309694, "min": 720.0, "max": 743.0, "median": 739.5, "filtered": 739.5, "mean": 735.5}, "Asteroids - Bitmaps- shapes- text": {"std": 71.23333138355947, "min": 888.0, "max": 1063.0, "median": 962.0, "filtered": 962.0, "mean": 968.75}, "Arena5 - Vectors- shadows- bitmaps- text": {"std": 73.40980860893181, "min": 738.0, "max": 920.0, "median": 853.0, "filtered": 853.0, "mean": 841.0}, "Asteroids - Vectors": {"std": 49.37294299512639, "min": 659.0, "max": 789.0, "median": 751.5, "filtered": 751.5, "mean": 737.75}, "3D Rendering - Maths- polygons- image transforms": {"std": 20.94486810653149, "min": 388.0, "max": 434.0, "median": 407.5, "filtered": 407.5, "mean": 409.25}, "Pixel blur - Math- getImageData- putImageData": {"std": 46.82680856090878, "min": 1435.0, "max": 1553.0, "median": 1491.0, "filtered": 1491.0, "mean": 1492.5}, "Asteroids - Bitmaps": {"std": 14.16642156650719, "min": 380.0, "max": 418.0, "median": 406.5, "filtered": 406.5, "mean": 402.75}}}, "test_machine": {"platform": "x86", "osversion": "Ubuntu 12.04", "os": "linux", "name": "talos-linux32-ix-040"}, "testrun": {"date": 1440091515, "suite": "tcanvasmark", "options": {"responsiveness": false, "tpmozafterpaint": false, "tpchrome": true, "tppagecycles": 1, "tpcycles": 5, "tprender": false, "shutdown": false, "cycles": 1, "rss": false}}, "test_build": {"name": "Firefox", "version": "43.0a1", "id": "20150820095841", "branch": "Mozilla-Inbound-Non-PGO", "revision": "bb85ec539217b9d3a5e83c40538d8565d292e72b"}}]

Filtering & Calculations

When the raw data comes in, we look for the summary tag in the json.

{"suite": 23.21740000000001, ... }

In this case we use 23.217 for the value inside of perfherder. This is the value that will be used for calculating alerts, displaying points on the graph, and for data when comparing two revisions.

In all cases there should be a 'subtests' field as well that lists out each page loaded along with a set of values:

"subtests": {"tresize": {"std": 0.7716690474213389, "min": 22.18191666666666, "max": 24.96453333333337, "median": 23.21740000000001, "filtered": 23.21740000000001, "mean": 23.254913333333334}

These values are used in the test specific view (not the suite summary). When viewing a graph, you can switch between different values for each data point to see what the mean, median, etc. are. This is where we get the fields. In addition, the default value is the 'filtered' value, this takes into account filters (ignore first 'x' data points, median|mean, etc.) on the raw data so we have summarized data being calculated at a single point.

Graph Server

Data is packaged as a file in an HTTP post object.

VALUES/AVERAGE

Two different types of data to be sent:

1. A single value to be stored as the 'average' in the test_runs table
2. A set of (interval, value) pairs to be stored in the test_run_values table, 'average' to be calculated by collector script

First type will be called 'AVERAGE' second called 'VALUES'. All data is formatted using comma separated notation.

date_run = seconds since epoch (linux time stamp) page_name = is unique to pages when combined with the pageset_id from test table

• for sending interval, value pairs

START
VALUES
machine_name,test_name,branch_name,ref_changeset,ref_build_id,date_run
interval0,value0,page_name0
interval1,value1,page_name1
...
intervalEND,valueEND,page_id
END

• for sending a single value

 START
 AVERAGE
 machine_name,test_name,branch_name,ref_changeset,ref_build_id,date_run
 value0
 END

Examples

values input:

START
VALUES
machine_1, test_1, branch_1, changeset_1, 13, 1229477017
1,1.0,page_01
2,2.0,page_02
3,3.0,page_03
4,1.0,page_04
5,2.0,page_05
6,3.0,page_06
7,1.0,page_07
8,2.0,page_08
9,3.0,page_09
10,1.0,page_10
11,2.0,page_11
12,3.0,page_12
END

response:

Content-type: text/plain 

RETURN\ttest_1\tgraph.html#type=series&tests=[{"test":45,"branch":3455,"machine":234,"testrun"=6667}]
RETURN\ttest_1\t2.00\tgraph.html#tests=[{"test":45,"branch":3455,"machine":234}]

average input:

START
AVERAGE
machine_1, test_1, branch_1, changeset_1, 13, 1229477017
2.0
END

response:

Content-type: text/plain

RETURN\ttest_1\t2.00\tgraph.html#tests=[{"test":45,"branch":3455,"machine":234}]

browser_output.txt

The data is harvested from browser_output.txt:

__start_tp_report
_x_x_mozilla_page_load,4070.909090909091,NaN,NaN
_x_x_mozilla_page_load_details,avgmedian|4070.909090909091|average|4070.73|minimum|NaN|maximum|NaN|stddev|NaN
|i|pagename|median|mean|min|max|runs|
|0;gearflowers.svg;162.5;163;162;226;226;165;163;162;162
|1;composite-scale.svg;77;77.25;77;115;115;77;77;78;77
|2;composite-scale-opacity.svg;31.5;31.75;30;62;62;31;34;30;32
|3;composite-scale-rotate.svg;31;31;29;60;60;29;32;33;30
|4;composite-scale-rotate-opacity.svg;31;31.5;29;36;35;31;31;29;36
|5;hixie-001.xml;15065;15063.75;15059;15086;15059;15065;15065;15066;15086
|6;hixie-002.xml;15064.5;15060.5;15047;15070;15070;15064;15066;15065;15047
|7;hixie-003.xml;5038;5038.75;5037;5054;5042;5037;5037;5054;5039
|8;hixie-004.xml;5081.5;5081.5;5079;5087;5087;5084;5079;5084;5079
|9;hixie-005.xml;6369.5;6367.5;6349;6405;6362;6405;6377;6382;6349
|10;hixie-006.xml;9270;9276;9239;9342;9239;9325;9278;9342;9262
|11;hixie-007.xml;3623.5;3619.25;3601;3653;3627;3629;3653;3601;3620
__end_tp_report
__start_cc_report
_x_x_mozilla_cycle_collect,1137
__end_cc_report
__startTimestamp1327556458940__endTimestamp
__startBeforeLaunchTimestamp1327556130230__endBeforeLaunchTimestamp
__startAfterTerminationTimestamp1327556459158__endAfterTerminationTimestamp