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From ju...@apache.org
Subject svn commit: r1488202 - /jackrabbit/oak/trunk/oak-run/README.md
Date Fri, 31 May 2013 13:25:00 GMT
Author: jukka
Date: Fri May 31 13:25:00 2013
New Revision: 1488202

URL: http://svn.apache.org/r1488202
OAK-641: Improved benchmark tooling

Add description of the benchmark tool


Added: jackrabbit/oak/trunk/oak-run/README.md
URL: http://svn.apache.org/viewvc/jackrabbit/oak/trunk/oak-run/README.md?rev=1488202&view=auto
--- jackrabbit/oak/trunk/oak-run/README.md (added)
+++ jackrabbit/oak/trunk/oak-run/README.md Fri May 31 13:25:00 2013
@@ -0,0 +1,89 @@
+Oak Runnable Jar
+Benchmark mode
+The oak-run jar has a "benchmark" mode for executing various micro-benchmarks.
+It can be invoked like this:
+    $ java -jar oak-run-*.jar benchmark [options] [testcases] [fixtures]
+The following benchmark options (with default values) are currently supported:
+    --host localhost   - MongoDB host
+    --port 27101       - MongoDB port
+    --cache 100        - cache size (in MB)
+    --wikipedia <file> - Wikipedia dump
+These options are passed to the test cases and repository fixtures
+that need them. For example the Wikipedia dump option is needed by the
+WikipediaImport test case and the MongoDB address information by the
+MongoMK and SegmentMK -based repository fixtures. The cache setting
+controls the bundle cache size in Jackrabbit, the KernelNodeState
+cache size in MongoMK and the default H2 MK, and the segment cache
+size in SegmentMK.
+You can use extra JVM options like `-Xmx` settings to better control the
+benchmark environment. It's also possible to attach the JVM to a
+profiler to better understand benchmark results. For example, I'm
+using `-agentlib:hprof=cpu=samples,depth=100` as a basic profiling
+tool, whose results can be processed with `perl analyze-hprof.pl
+java.hprof.txt` to produce a somewhat easier-to-read top-down and
+bottom-up summaries of how the execution time is distributed across
+the benchmarked codebase.
+The test case names like `ReadPropertyTest`, `SmallFileReadTest` and
+`SmallFileWriteTest` indicate the specific test case being run. You can
+specify one or more test cases in the benchmark command line, and
+oak-run will execute each benchmark in sequence. The benchmark code is
+located under `org.apache.jackrabbit.oak.benchmark` in the oak-run
+component. Each test case tries to exercise some tightly scoped aspect
+of the repository. You might remember many of these tests from the
+Jackrabbit benchmark reports like
+that we used to produce earlier.
+Finally the benchmark runner supports the following repository fixtures:
+| Fixture     | Description                                           |
+| Jackrabbit  | Jackrabbit with the default embedded Derby  bundle PM |
+| Oak-Memory  | Oak with the default MK using in-memory storage       |
+| Oak-Default | Oak with the default MK using embedded H2 database    |
+| Oak-Mongo   | Oak with the new MongoMK                              |
+| Oak-Segment | Oak with MongoDB-based SegmentMK                      |
+| Oak-Tar     | Oak with Tar file -based SegmentMK                    |
+Once started, the benchmark runner will execute each listed test case
+against all the listed repository fixtures. After starting up the
+repository and preparing the test environment, the test case is first
+executed a few times to warm up caches before measurements are
+started. Then the test case is run repeatedly for one minute (or at
+least 10 times) and the number of milliseconds used by each execution
+is recorded. Once done, the following statistics are computed and
+| Column      | Description                                           |
+| min         | minimum time (in ms) taken by a test run              |
+| 10%         | time (in ms) in which the fastest 10% of test runs    |
+| 50%         | time (in ms) taken by the median test run             |
+| 90%         | time (in ms) in which the fastest 90% of test runs    |
+| max         | maximum time (in ms) taken by a test run              |
+| N           | total number of test runs in one minute (or more)     |
+The most useful of these numbers is probably the 90% figure, as it
+shows the time under which the majority of test runs completed and
+thus what kind of performance could reasonably be expected in a normal
+usage scenario. However, the reason why all these different numbers
+are reported, instead of just the 90% one, is that often seeing the
+distribution of time across test runs can be helpful in identifying
+things like whether a bigger cache might help.
+Finally, and most importantly, like in all benchmarking, the numbers
+produced by these tests should be taken with a large dose of salt.
+They DO NOT directly indicate the kind of application performance you
+could expect with (the current state of) Oak. Instead they are
+designed to isolate implementation-level bottlenecks and to help
+measure and profile the performance of specific, isolated features.

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