Cross joins should be handled like outer joins in the join order
optimization in that the right table referenced by a cross join may not
be reordered anywhere before tables referenced to the left of the cross
join. If there are inner joins to the right of the cross join, those
tables may be reordered before the cross join.
E.g., if we have A JOIN B CROSS JOIN C JOIN D, then C must come after A
and B, but D may be reordered to come before C.
Also adds test cases for join order optimization and predicate propagation.
Change-Id: I6b1022dd3e862efbff81e283b43284d846c8eca4
Reviewed-on: http://gerrit.ent.cloudera.com:8080/1096
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: jenkins
Adds a CROSS JOIN (cartesian product). Common join code is moved from to
a new abstract base class BlockingJoinNode. We must keep all build RowBatches in
memory in order to iterate over them for every row from the left child. The
TupleRowList provides a convenient way to iterate over all of the rows.
A future change will address codegen for the CrossJoinNode.
Change-Id: I5e0caa6fb4ec802a9c87e700f9dd6238cea8cdf2
Reviewed-on: http://gerrit.ent.cloudera.com:8080/970
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: jenkins
Fixed the following stats-related bugs:
- Per-partition row count was not distributed properly via CatalogService
- HBase column stats were not loaded and distributed properly
Enhancements to test framework:
- Allow regex specification of expected row or column values
- Fixed expected results of some tests because the test framework
did not catch that they were incorrect
Change-Id: I1fa8e710bbcf0ddb62b961fdd26ecd9ce7b75d51
Reviewed-on: http://gerrit.ent.cloudera.com:8080/813
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: jenkins
This is the first set of changes required to start getting our functional test
infrastructure moved from JUnit to Python. After investigating a number of
option, I decided to go with a python test executor named py.test
(http://pytest.org/). It is very flexible, open source (MIT licensed), and will
enable us to do some cool things like parallel test execution.
As part of this change, we now use our "test vectors" for query test execution.
This will be very nice because it means if load the "core" dataset you know you
will be able to run the "core" query tests (specified by --exploration_strategy
when running the tests).
You will see that now each combination of table format + query exec options is
treated like an individual test case. this will make it much easier to debug
exactly where something failed.
These new tests can be run using the script at tests/run-tests.sh
This change updates the run-benchmark script to enable it to target one or more
workloads. Now benchmarks can be run like:
./run-benchmark --workloads=hive-benchmark,tpch
We lookup the workload in the workloads directory, then read the associated
query .test files and start executing them.
To ensure the queries are not duplicated between benchmark and query tests, I
moved all existing queries (under fe/src/test/resources/* to the workloads
directory. You do NOT need to look through all the .test files, I've just moved
them. The one new file is the 'hive-benchmark.test' which contains the hive
benchmark queries.
Also added support for generating schema for different scale factors as well as
executing against these scale factors. For example, let's say we have a dataset
with a scale factor called "SF1". We would first generate the schema using:
./generate_schema_statements --workload=<workload> --scale_factor="SF3"
This will create tables with a unique names from the other scale factors.
Run the generated .sql file to load the data. Alternatively, the data can loaded
by running a new python script:
./bin/load-data.py -w <workload1>,<workload2> -e <exploration strategy> -s [scale factor]
For example: load-data.sh -w tpch -e core -s SF3
Then run against this:
./run-benchmark --workloads=<workload> --scale_factor=SF3
This changeset also includes a few other minor tweaks to some of the test
scripts.
Change-Id: Ife8a8d91567d75c9612be37bec96c1e7780f50d6
