I’m not sure there are any — and you’re right, there probably should.
Having said that, integration is very straight-forward. You run pyspark (or spark-submit), passing in the Ignite jar files (using the —jars parameter). For example: $SPARK_HOME/bin/spark-submit --jars $IGNITE_HOME/libs/ignite-spring/*.jar,$IGNITE_HOME/libs/optional/ignite-spark/ignite-*.jar,$IGNITE_HOME/libs/*.jar,$IGNITE_HOME/libs/ignite-indexing/*.jar --master spark://spark-master:7077 /opt/bin/sample-python.py (I probably included more JAR files than strictly necessary.) And that’s kind of it. Ignite caches are exposed as a DataFrames. Other that the options to connect that I mentioned in my previous post, there aren’t really any special incantations or anything interesting to document. In that sense, almost any PySpark tutorial would do the trick. Regards, Stephen > On 17 Dec 2018, at 03:42, anthonycwmak <anthonycw...@gmail.com> wrote: > > Thanks for that Stephen. That is a start. > > Would you know any documentation/tutorials/examples for Ignite and Spark > integration (**in Python**)? > > Anthony > > > > -- > Sent from: http://apache-ignite-users.70518.x6.nabble.com/
