Russell Spitzer created SPARK-16614:
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Summary: DirectJoin with DataSource for SparkSQL
Key: SPARK-16614
URL: https://issues.apache.org/jira/browse/SPARK-16614
Project: Spark
Issue Type: New Feature
Components: SQL
Affects Versions: 2.0.0
Reporter: Russell Spitzer
Join behaviors against some datasources can be improved by skipping a full scan
and instead performing a series of point lookups.
An example
{code}DataFrame A contains { key1, key5, key302, ... key 50923423}
DataFrame B is a source reading from a C* database with keys {key1, key2,
key3 ....}
a.join(b){code}
Currently this will cause the entirety of the DataFrame B to be read into
memory before performing a Join. Instead it would be useful if we could expose
another api, {{DirectJoinSource}} which allowed connectors to provide a means
of requests a non-contiguous subset of keys from a DataSource.
This kind of lookup would behave like the joinWithCasandraTable call in the
Spark Cassandra Connector
https://github.com/datastax/spark-cassandra-connector/blob/master/doc/2_loading.md#using-joinwithcassandratable.
We find that this is much more useful when the end user is requesting only a
small portion of well defined records. I believe this could be applicable to a
variety of datasources where reading the entire source is inefficient compared
to point lookups.
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