GitHub user nongli reopened a pull request:
https://github.com/apache/spark/pull/10628
[SPARK-12635][SQL] Add ColumnarBatch, an in memory columnar format for
execution.
There are many potential benefits of having an efficient in memory columnar
format as an alternate
to UnsafeRow. This patch introduces ColumnarBatch/ColumnarVector which
starts this effort. The
remaining implementation can be done as follow up patches.
As stated in the in the JIRA, there are useful external components that
operate on memory in a
simple columnar format. ColumnarBatch would serve that purpose and could
server as a
zero-serialization/zero-copy exchange for this use case.
This patch supports running the underlying data either on heap or off heap.
On heap runs a bit
faster but we would need offheap for zero-copy exchanges. Currently, this
mode is hidden behind one
interface (ColumnVector).
This differs from Parquet or the existing columnar cache because this is
*not* intended to be used
as a storage format. The focus is entirely on CPU efficiency as we expect
to only have 1 of these
batches in memory per task. The layout of the values is just dense arrays
of the value type.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/nongli/spark spark-12635
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/10628.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 #10628
----
commit 84c657bdbc19105608e0d07fd59587b84eaaebcf
Author: Nong <non...@gmail.com>
Date: 2016-01-01T05:12:44Z
[SPARK-12635][SQL] Add ColumnarBatch, an in memory columnar format for
execution.
There are many potential benefits of having an efficient in memory columnar
format as an alternate
to UnsafeRow. This patch introduces ColumnarBatch/ColumnarVector which
starts this effort. The
remaining implementation can be done as follow up patches.
As stated in the in the JIRA, there are useful external components that
operate on memory in a
simple columnar format. ColumnarBatch would serve that purpose and could
server as a
zero-serialization/zero-copy exchange for this use case.
This patch supports running the underlying data either on heap or off heap.
On heap runs a bit
faster but we would need offheap for zero-copy exchanges. Currently, this
mode is hidden behind one
interface (ColumnVector).
This differs from Parquet or the existing columnar cache because this is
*not* intended to be used
as a storage format. The focus is entirely on CPU efficiency as we expect
to only have 1 of these
batches in memory per task.
commit c547ec5df19fcd8dbd1becdd4fa98fd6246d5732
Author: Nong Li <n...@databricks.com>
Date: 2016-01-07T05:14:08Z
CR
commit 48574de403e05c3d3833356056eb88eb3c286d29
Author: Nong Li <n...@databricks.com>
Date: 2016-01-12T00:40:26Z
Fix double put api.
commit 91b6fc04fd6100ce14f1bab1fb2893464c79fbbf
Author: Nong Li <n...@databricks.com>
Date: 2016-01-12T02:06:30Z
Fix imports and rebase.
commit 36c8ddb6b51b3a7ee33950732287644a758615e7
Author: Nong Li <n...@databricks.com>
Date: 2016-01-12T05:52:08Z
Support java 7 iterator interface.
----
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