The Spark Cassandra Connector is built using sbt. There is a premade
launching script for sbt so it is unneccessary to download it. To invoke
this script you can run ./sbt/sbt
from a clone of this repository.
For information on setting up your clone please follow the Github Help
Once in the sbt shell you will be able to build and run tests for the connector without any Spark or Cassandra nodes running. The most common commands to use when developing the connector are
test
- Runs the the unit tests for the project.it:test
- Runs the integeration tests with embedded C* and Sparkassembly
- Builds a fat jar for using with --jars in spark submit or spark-shell
The integration tests located in spark-cassandra-connector/src/it
should
probably be the first place to look for anyone considering adding code.
There are many examples of executing a feature of the connector with
the embedded Cassandra and Spark nodes and are the core of our test
coverage.
The connector currently contains several subprojects
This sub project contains all of the actual connector code and is where any new features or tests should go. This Scala project also contains the Java api and related code.
The code used to start the embedded services used in the integration tests. This contains methods for starting up C* as a thread within the running test code.
Code for building reference documentation. This uses the code from
spark-cassandra-connector
to determine what belongs in the reference
file. It should mostly be used for regenerating the reference file after
new parameters have been added or old parameters have been changed. Tests
in spark-cassandra-connector
will throw errors if the reference file is
not up to date. To fix this run spark-cassandra-connector-doc/run
to
update the file. It is still necessary to commit the changed file after
running this sub-project.
Code for performance based tests. Add any performance comparisons needed to this project.
It's often useful when implementing new features to have the tests run
in a loop on code change. Sbt provides a method for this by using the
~
operator. With this ~ test
will run the unit tests every time a
change in the source code is detected. This is often useful to use in
conjunction with testOnly
which runs a single test. So if a new feature
were being added to the integration suite foo
you may want to run
~ it:testOnly foo
. Which would only run the suite you are interested in
on a loop while you are modifying the connector code.
The spark-shell
and spark-submit
are able to use local caches to load
libraries and this can be taken advantage of by the SCC. For example
if you wanted to test the maven artifacts produced for your current build
you could run publishM2
which would generate the needed artifacts and
pom in your local cache. You can then reference this from spark-shell
or spark-submit
using the following code
./bin/spark-shell --repositories file:/Users/yourUser/.m2/repository --packages com.datastax.spark:spark-cassandra-connector_2.10:1.6.0-14-gcfca49e
Where you would change the revision 1.6.0-14-gcfca49e
to match the output
of your publish command.
This same method should work with publishLocal
after the merging of SPARK-12666