Re: Issues with controlling partitions when using Apache Spark


Hi Mladen,

Having answered several questions about the JanusGraph InputFormats, I can confirm that many users encounter problems with the size of the input splits. This is the case in particular for the HBaseInputFormat where input splits are equal to HBase regions and HBase requires regions to have a size of the order of 10GB (compressed binary data!). Users could only work around this by manually and temporarily splitting the HBase regions. For the CassandraInputFormat problems surface less often, because there a default number of about 500 partitions is used, so you need a lot of data before partition size becomes a limitation.

So, I also encourage you to contribute, if possible!

Also note that there is a fundamental problem to OLAP in graphs: traversing a graph implies shuffling between partitions and this is only efficient if the entire graph fits in the cluster memory. So, where the scalability of JanusGraph OLTP queries is limited by disk space and the performance of the indexing backend, the scalability of OLAP queries is limited by cluster memory.

Best wishes,    Marc

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