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author | Eric Liang <ekl@databricks.com> | 2016-06-20 21:56:44 -0700 |
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committer | Reynold Xin <rxin@databricks.com> | 2016-06-20 21:56:44 -0700 |
commit | 07367533de68817e1e6cf9cf2b056a04dd160c8a (patch) | |
tree | f17e98e0577711b9741213a6eb33eb2e2800783d /docs | |
parent | 4f7f1c436205630ab77d3758d7210cc1a2f0d04a (diff) | |
download | spark-07367533de68817e1e6cf9cf2b056a04dd160c8a.tar.gz spark-07367533de68817e1e6cf9cf2b056a04dd160c8a.tar.bz2 spark-07367533de68817e1e6cf9cf2b056a04dd160c8a.zip |
[SPARK-16025][CORE] Document OFF_HEAP storage level in 2.0
This has changed from 1.6, and now stores memory off-heap using spark's off-heap support instead of in tachyon.
Author: Eric Liang <ekl@databricks.com>
Closes #13744 from ericl/spark-16025.
Diffstat (limited to 'docs')
-rw-r--r-- | docs/programming-guide.md | 5 |
1 files changed, 5 insertions, 0 deletions
diff --git a/docs/programming-guide.md b/docs/programming-guide.md index 97bcb511b2..3872aecff2 100644 --- a/docs/programming-guide.md +++ b/docs/programming-guide.md @@ -1220,6 +1220,11 @@ storage levels is: <td> MEMORY_ONLY_2, MEMORY_AND_DISK_2, etc. </td> <td> Same as the levels above, but replicate each partition on two cluster nodes. </td> </tr> +<tr> + <td> OFF_HEAP (experimental) </td> + <td> Similar to MEMORY_ONLY_SER, but store the data in + <a href="configuration.html#memory-management">off-heap memory</a>. This requires off-heap memory to be enabled. </td> +</tr> </table> **Note:** *In Python, stored objects will always be serialized with the [Pickle](https://docs.python.org/2/library/pickle.html) library, |