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| -rw-r--r-- | docs/sql-programming-guide.md | 7 |
1 files changed, 7 insertions, 0 deletions
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 9f87accd30..3f9a831edd 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -1233,6 +1233,13 @@ infer the data types of the partitioning columns. For these use cases, the autom can be configured by `spark.sql.sources.partitionColumnTypeInference.enabled`, which is default to `true`. When type inference is disabled, string type will be used for the partitioning columns. +Starting from Spark 1.6.0, partition discovery only finds partitions under the given paths +by default. For the above example, if users pass `path/to/table/gender=male` to either +`SQLContext.read.parquet` or `SQLContext.read.load`, `gender` will not be considered as a +partitioning column. If users need to specify the base path that partition discovery +should start with, they can set `basePath` in the data source options. For example, +when `path/to/table/gender=male` is the path of the data and +users set `basePath` to `path/to/table/`, `gender` will be a partitioning column. ### Schema Merging |