Please vote on releasing the following candidate as Apache Spark version
2.3.2.
The vote is open until July 11th PST and passes if a majority +1 PMC votes
are cast, with a minimum of 3 +1 votes.
[ ] +1 Release this package as Apache Spark 2.3.2
[ ] -1 Do not release this package because ...
To l
We've created a snippet that creates a Spark DF from a RDD of many pandas
DFs in a distributed manner that does not require the driver to collect the
entire dataset.
Early tests show a performance improvement of x6-x10 over using
pandasDF->Rows>sparkDF.
I've seen that there are some open pull req
Hi Linar,
This seems useful. But perhaps reusing the same function name is better?
http://spark.apache.org/docs/2.1.0/api/python/pyspark.sql.html#pyspark.sql.SparkSession.createDataFrame
Currently createDataFrame takes an RDD of any kind of SQL data
representation(e.g. row, tuple, int, boolean,
Hi All,
I would like to invite you to review the design document for Barrier
Execution Mode:
https://docs.google.com/document/d/1GvcYR6ZFto3dOnjfLjZMtTezX0W5VYN9w1l4-tQXaZk/edit#
TL;DR: We announced the project Hydrogen on recent Spark+AI Summit, a major
part of the project involves significant c
Just checking that the doc issue in
https://issues.apache.org/jira/browse/SPARK-24530 is worked around in this
release?
This was pointed out as an example of a broken doc:
https://spark.apache.org/docs/2.3.1/api/python/pyspark.ml.html#pyspark.ml.classification.LogisticRegression
Here it is in 2.3
Xingbo,
Please reference the spip and jira ticket next time: [SPARK-24374] SPIP:
Support Barrier Scheduling in Apache Spark
On Sun, Jul 8, 2018 at 9:45 AM Xingbo Jiang wrote:
> Hi All,
>
> I would like to invite you to review the design document for Barrier
> Execution Mode:
>
> https://docs.g
Yes I would just reuse the same function.
On Sun, Jul 8, 2018 at 5:01 AM Li Jin wrote:
> Hi Linar,
>
> This seems useful. But perhaps reusing the same function name is better?
>
>
> http://spark.apache.org/docs/2.1.0/api/python/pyspark.sql.html#pyspark.sql.SparkSession.createDataFrame
>
> Curren
Three business days might be too short. Let us open the vote until the end
of this Friday (July 13th)?
Cheers,
Xiao
2018-07-08 10:15 GMT-07:00 Sean Owen :
> Just checking that the doc issue in https://issues.apache.org/
> jira/browse/SPARK-24530 is worked around in this release?
>
> This was po
Hi Sean,
SPARK-24530 is not included in this RC1 release. Actually I'm so familiar
with this issue so still using python2 to generate docs.
In the JIRA it mentioned that python3 with sphinx could workaround this
issue. @Hyukjin Kwon would you please help to clarify?
Thanks
Saisai
Xiao Li 于20
Seems Python 2's Sphinx was used -
https://dist.apache.org/repos/dist/dev/spark/v2.3.2-rc1-docs/_site/api/python/pyspark.ml.html#pyspark.ml.classification.LogisticRegression
and SPARK-24530 issue exists in the RC. it's kind of tricky to manually
verify if Python 3 is used given my few tries in my l
Thanks @Hyukjin Kwon . Yes I'm using python2 to build
docs, looks like Python2 with Sphinx has issues.
What is the pending thing for this PR (
https://github.com/apache/spark/pull/21659)? I'm planning to cut RC2 once
this is merged, do you an ETA for this PR?
Hyukjin Kwon 于2018年7月9日周一 上午9:06写道:
The reason is that it is not 100% clear if the root cause in the Sphinx bug
is Python 2 and if the workaround is to use Python 3. Xiangrui opened a bug
against Sphinx https://github.com/sphinx-doc/sphinx/issues/5142
Here is my observation:
- Sphinx seems having a bug that it does not respect
'auto
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