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| author | Andrew Or <andrew@databricks.com> | 2016-05-19 23:44:10 -0700 |
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| committer | Andrew Or <andrew@databricks.com> | 2016-05-19 23:44:10 -0700 |
| commit | c32b1b162e7e5ecc5c823f79ba9f23cbd1407dbf (patch) | |
| tree | 534f6d61bc843adf1ebd4682e5df27d45b6dba72 /streaming | |
| parent | 257375019266ab9e3c320e33026318cc31f58ada (diff) | |
| download | spark-c32b1b162e7e5ecc5c823f79ba9f23cbd1407dbf.tar.gz spark-c32b1b162e7e5ecc5c823f79ba9f23cbd1407dbf.tar.bz2 spark-c32b1b162e7e5ecc5c823f79ba9f23cbd1407dbf.zip | |
[SPARK-15417][SQL][PYTHON] PySpark shell always uses in-memory catalog
## What changes were proposed in this pull request?
There is no way to use the Hive catalog in `pyspark-shell`. This is because we used to create a `SparkContext` before calling `SparkSession.enableHiveSupport().getOrCreate()`, which just gets the existing `SparkContext` instead of creating a new one. As a result, `spark.sql.catalogImplementation` was never propagated.
## How was this patch tested?
Manual.
Author: Andrew Or <andrew@databricks.com>
Closes #13203 from andrewor14/fix-pyspark-shell.
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