c766f50491
"
The debug mode unit tests take ~half-an-hour to complete. Here's
the tests run-times top list
Test: Time (seconds):
... steady tail goes here ...
test/boost/user_function_test 496
test/boost/row_cache_test 502
test/boost/view_schema_test 932
test/boost/cql_query_test 997
test/boost/mutation_reader_test 1048
test/boost/sstable_mutation_test 1417
test/boost/secondary_index_test 1468
Splitting the spike (top-5) is the primary goal. However, the
distribution of test-cases in 3 of those tests is also _very_
non-uniform, so just cutting it into equal parts doesn't work.
For example, the test_index_with_paging from the slowest one
takes ~14 minutes on its own and is the slowest test-case out
there.
So the set does this:
- moves the champion test_index_with_paging into separate file
- detaches the most heavy parts from sstable_mutation_test and
mutation_reader_test into own tests too. The resulting split
is still non-uniform, but it's 4 tests that run notably less
than the 14 minutes record each
- splits the cql_query_test and view_schema_test into several
parts in a wildcard manner to run out of the 14 min threshold
- moves some shared code into lib/
As the result, the debug mode test run takes 14.5 minutes =)
which is almost 2 times faster than it was. The dev mode run
time is not affected noticeably.
Test: well, unit(debug) and unit(dev)
"
* 'br-split-unit-tests-3-next' of https://github.com/xemul/scylla:
test: Split view_schema_test
test: Split cql_query_test
test: Split mutation_reader_test
test: Split sstable_mutation_test
test: Split secondary_index test
Scylla
Quick-start
To get the build going quickly, Scylla offers a frozen toolchain which would build and run Scylla using a pre-configured Docker image. Using the frozen toolchain will also isolate all of the installed dependencies in a Docker container. Assuming you have met the toolchain prerequisites, which is running Docker in user mode, building and running is as easy as:
$ ./tools/toolchain/dbuild ./configure.py
$ ./tools/toolchain/dbuild ninja build/release/scylla
$ ./tools/toolchain/dbuild ./build/release/scylla --developer-mode 1
Please see HACKING.md for detailed information on building and developing Scylla.
Note: GCC >= 8.1.1 is required to compile Scylla.
Running Scylla
- Run Scylla
./build/release/scylla
- run Scylla with one CPU and ./tmp as work directory
./build/release/scylla --workdir tmp --smp 1
- For more run options:
./build/release/scylla --help
Testing
See test.py manual.
Scylla APIs and compatibility
By default, Scylla is compatible with Apache Cassandra and its APIs - CQL and Thrift. There is also experimental support for the API of Amazon DynamoDB, but being experimental it needs to be explicitly enabled to be used. For more information on how to enable the experimental DynamoDB compatibility in Scylla, and the current limitations of this feature, see Alternator and Getting started with Alternator.
Documentation
Documentation can be found in ./docs and on the wiki. There is currently no clear definition of what goes where, so when looking for something be sure to check both. Seastar documentation can be found here. User documentation can be found here.
Training
Training material and online courses can be found at Scylla University. The courses are free, self-paced and include hands-on examples. They cover a variety of topics including Scylla data modeling, administration, architecture, basic NoSQL concepts, using drivers for application development, Scylla setup, failover, compactions, multi-datacenters and how Scylla integrates with third-party applications.
Building Fedora-based Docker image
Build a Docker image with:
cd dist/docker
docker build -t <image-name> .
Run the image with:
docker run -p $(hostname -i):9042:9042 -i -t <image name>