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| author | Sunitha Kambhampati <skambha@us.ibm.com> | 2017-02-13 22:49:29 -0800 |
|---|---|---|
| committer | Xiao Li <gatorsmile@gmail.com> | 2017-02-13 22:49:29 -0800 |
| commit | 9b5e460a9168ab78607034434ca45ab6cb51e5a6 (patch) | |
| tree | 17dda1ff9cf275bf389e88865e37b8a1496cbea6 /docs | |
| parent | 1ab97310e83ee138a1b210c0dfa89a341f1d530a (diff) | |
| download | spark-9b5e460a9168ab78607034434ca45ab6cb51e5a6.tar.gz spark-9b5e460a9168ab78607034434ca45ab6cb51e5a6.tar.bz2 spark-9b5e460a9168ab78607034434ca45ab6cb51e5a6.zip | |
[SPARK-19585][DOC][SQL] Fix the cacheTable and uncacheTable api call in the doc
## What changes were proposed in this pull request?
https://spark.apache.org/docs/latest/sql-programming-guide.html#caching-data-in-memory
In the doc, the call spark.cacheTable(“tableName”) and spark.uncacheTable(“tableName”) actually needs to be spark.catalog.cacheTable and spark.catalog.uncacheTable
## How was this patch tested?
Built the docs and verified the change shows up fine.
Author: Sunitha Kambhampati <skambha@us.ibm.com>
Closes #16919 from skambha/docChange.
Diffstat (limited to 'docs')
| -rw-r--r-- | docs/sql-programming-guide.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 9cf480caba..235f5ecc40 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -1272,9 +1272,9 @@ turning on some experimental options. ## Caching Data In Memory -Spark SQL can cache tables using an in-memory columnar format by calling `spark.cacheTable("tableName")` or `dataFrame.cache()`. +Spark SQL can cache tables using an in-memory columnar format by calling `spark.catalog.cacheTable("tableName")` or `dataFrame.cache()`. Then Spark SQL will scan only required columns and will automatically tune compression to minimize -memory usage and GC pressure. You can call `spark.uncacheTable("tableName")` to remove the table from memory. +memory usage and GC pressure. You can call `spark.catalog.uncacheTable("tableName")` to remove the table from memory. Configuration of in-memory caching can be done using the `setConf` method on `SparkSession` or by running `SET key=value` commands using SQL. |