Github user dongjoon-hyun commented on the issue:
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Then, @rxin and @gatorsmile .
I'll make a PR to merge `maxConnection` into `numPartitions`.
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Github user gatorsmile commented on the issue:
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My fault. In my initial thoughts, `numPartitions` does not indicate the max
allowed number of JDBC connections, and the write path does not always create
the exact number of partitions. We only
Github user dongjoon-hyun commented on the issue:
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The rational is to give a name which has a clear meaning. Also, I agreed
with the following advice.
> numPartitions might be not a good name for this purpose. How about
Github user rxin commented on the issue:
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Basically right now if I were to define a table, I'd need to define both
the read and the write side, using numPartitions and maxPartitions. Even if we
want to have two separate configs for read vs
Github user dongjoon-hyun commented on the issue:
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The code seems to be gone during resolving conflicts. This is the my
comment at the first review.
> Thank you for review, @srowen .
>
> First, the property numPartitions
Github user rxin commented on the issue:
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Got it - so this is to enforce the write side: in the future please make it
clear this is for the write side.
Coming back to the discussion: shouldn't we just use numPartitions, given
it is
Github user dongjoon-hyun commented on the issue:
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Let me find the correct code. (It's weird I attached a wrong code example.)
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Yes - otherwise it can get pretty confusing.
I'd argue the user has already explicitly defined the degree of parallelism
in the JDBC source using other options. Having this maxConnections
Github user dongjoon-hyun commented on the issue:
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Hi, @rxin .
Do you mean changing SQL syntax like `BROADCAST HINT` PR we tried before?
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It's read-only option. At the first commit, I reuse that option for
writing. But, as you see, it changed according the review advices.
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Don't they already specify "numPartitions" ?
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Could you give the example of existing method you mention?
> the user has already explicitly defined the degree of parallelism in the
JDBC source using other options.
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Github user rxin commented on the issue:
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Hm - wouldn't a more general solution be to introduce a parallelism hint or
command (basically the coalesce equivalent) in SQL?
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Thank you for review and merging, @srowen , @gatorsmile , @cloud-fan ,
@lichenglin !
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Merged to master
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LGTM, waiting @srowen for final sign off
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Hi, @cloud-fan .
If there is something to do more, please let me know again.
Thank you so much.
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Retest this please.
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It seems not a test failure.
```
Traceback (most recent call last):
File "./dev/run-tests-jenkins.py", line 232, in
main()
File "./dev/run-tests-jenkins.py", line
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retest this please
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Thank you, @srowen !
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Hi, @srowen .
Could you review this PR again?
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LGTM
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Documentation and PR descriptions are updated.
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Yeah, please improve the document comments and PR descriptions.
It sounds like this is almost ready to merge after these changes.
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Ah, right. Now always!
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> This option applies only to writing with additional coalesce operation.
It is not clear. We do not always call `coalesce`. : )
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For document, may I add more description about the behavior to help the
user understanding?
**BEFORE**
> The number of JDBC connections, which specifies the maximum number of
Github user dongjoon-hyun commented on the issue:
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Thank you for review again, @cloud-fan , @liancheng , and @srowen .
I had the same opinion with @srowen . Also, let's think about the
background of this issue.
Currently, in
Github user srowen commented on the issue:
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Conceptually, it does seem nicer to resolve this with a connection pool.
There is however some complexity in implementing our own connection pool.
I think you've pointed out a key issue:
Github user lichenglin commented on the issue:
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In fact,I have idea .
We can change the param to "connections pool size on each executor",every
partition task on the same executor use the same connection pool to save data.
we can
Github user srowen commented on the issue:
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I see, because a user can specify this option through SQL only? Ok, then
that logic makes sense to me.
It's still kinda a coarse way to achieve a limit on concurrent connections.
Some
Github user cloud-fan commented on the issue:
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> We cannot call repartition in SQL language environment
This is a good point, we need to provide a workaround for sql users, and
this PR did.
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Sorry for late response, @gatorsmile and @srowen .
---
> However, when users use the DataFrameWriter, this is not available.
Maybe, in the future, we can add another option
Github user gatorsmile commented on the issue:
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FYI, SQOOP2 also [adds a
feature](http://blog.cloudera.com/blog/2012/01/apache-sqoop-highlights-of-sqoop-2/)
for limiting the max number of connections:
> By limiting the total number
Github user gatorsmile commented on the issue:
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Yeah, although we change the operator from `repartition` to `coalesce`, but
yeah still costly.
When users use JDBC source to connect RDBMS, the max number of concurrent
connections is
Github user srowen commented on the issue:
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OK I have an overall question about this approach. The point is to limit
concurrent JDBC connections? this does that, but, requires repartitioning data
to accomplish that, which is expensive. One
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Github user gatorsmile commented on the issue:
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LGTM. Maybe @srowen and @cloud-fan can double check the code.
BTW, in the code path of regular SQL, we are able to explain the
INSERT/CTAS. However, when users use the DataFrameWriter,
Github user dongjoon-hyun commented on the issue:
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Thank you, @gatorsmile . I added the negative test case.
But, for the positive test case, `DataFrameWriter` keeps it `private` and
`save` function returns `Unit`.
```scala
private
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Yeah, add one negative test case and one positive test case for the newly
added parm. For example, below is a negative test case.
```
val df =
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Could you review this PR again, @gatorsmile?
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I rebased and squashed to resolve conflicts. The PR is updated the
followings.
- Revert `DataSource.scala` change.
- Rename `JDBC_MAX_CONNECTION` to `JDBC_MAX_CONNECTIONS`.
- Add
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Hi, @gatorsmile .
Indeed, I really want to add a test case for this.
Could you give me some advice how to test this kind of features?
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Just FYI, the only failure is irrelevant.
```
[info] StateStoreSuite:
[info] - maintenance *** FAILED *** (10 seconds, 120 milliseconds)
[info] The code passed to eventually
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Could we have a test case for this new parameter?
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LGTM except one minor comment. Also CC @cloud-fan
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Hi, @srowen and @gatorsmile .
How do you think about the updated PR?
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Thank you for retriggering, @gatorsmile .
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retest this please
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Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/15868
@gatorsmile , I addressed all comments.
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/15868
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