GitHub user jmahonin opened a pull request:
https://github.com/apache/phoenix/pull/63
PHOENIX-1815 Use Spark Data Source API in phoenix-spark module
This allows using the SQLContext.load() functionality to create
a Phoenix data frame, which also supports push-down on column
or predicate filtering from Spark SQL.
As well, DataFrame.save() is supported for persisting DataFrames
back to Phoenix.
This may work with Spark's standalone SQL server mode, but it
hasn't been tested.
ref:
https://spark.apache.org/docs/latest/sql-programming-guide.html#data-sources
https://databricks.com/blog/2015/01/09/spark-sql-data-sources-api-unified-data-access-for-the-spark-platform.html
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/FileTrek/phoenix PHOENIX-1815
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/phoenix/pull/63.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #63
----
commit c62178a1016a7885bd2c082fd1380c9a3023ca34
Author: Josh Mahonin <jmaho...@gmail.com>
Date: 2015-03-25T19:40:10Z
PHOENIX-1815 Use Spark Data Source API in phoenix-spark module
This allows using the SQLContext.load() functionality to create
a Phoenix data frame, which also supports push-down on column
or predicate filtering from Spark SQL.
As well, DataFrame.save() is supported for persisting DataFrames
back to Phoenix.
This may work with Spark's standalone SQL server mode, but it
hasn't been tested.
ref:
https://spark.apache.org/docs/latest/sql-programming-guide.html#data-sources
https://databricks.com/blog/2015/01/09/spark-sql-data-sources-api-unified-data-access-for-the-spark-platform.html
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