Commit Graph

8 Commits

Author SHA1 Message Date
ishaan
53cd9eadab Treat HBase as a file format for functional tests
Change-Id: Ia01181a1e10eb108419122d347e9d869a69e8922
Reviewed-on: http://gerrit.ent.cloudera.com:8080/102
Reviewed-by: Ishaan Joshi <ishaan@cloudera.com>
Tested-by: Ishaan Joshi <ishaan@cloudera.com>
2014-01-08 10:52:36 -08:00
Nong Li
563cbfa3a8 Enable parquet testing 2014-01-08 10:49:40 -08:00
Skye Wanderman-Milne
461a48df2b Refactor testing framework to generate Avro tables. 2014-01-08 10:48:45 -08:00
ishaan
09d6d931f4 Change the way data is loaded 2014-01-08 10:48:09 -08:00
Nong Li
02c329b97a Update RC files to use io mgr and remove scanner support for non-io mgr. 2014-01-08 10:47:11 -08:00
Lenni Kuff
e10960b2c9 Disable test execution against Trevni and replace with seq/snap format 2014-01-08 10:47:10 -08:00
Lenni Kuff
ef48f65e76 Add test framework for running Impala query tests via Python
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
2014-01-08 10:46:50 -08:00
Lenni Kuff
04edc8f534 Update benchmark tests to run against generic workload, data loading with scale factor, +more
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
2014-01-08 10:44:22 -08:00