[jira] [Created] (ARROW-1439) [Packaging] Automate updating RPM in RPM build

Kouhei Sutou created ARROW-1439: --- Summary: [Packaging] Automate updating RPM in RPM build Key: ARROW-1439 URL: https://issues.apache.org/jira/browse/ARROW-1439 Project: Apache Arrow Issue Type:

[jira] [Created] (ARROW-1438) [Plasma] Pull SerializationContext through PlasmaClient put and get

Philipp Moritz created ARROW-1438: - Summary: [Plasma] Pull SerializationContext through PlasmaClient put and get Key: ARROW-1438 URL: https://issues.apache.org/jira/browse/ARROW-1438 Project: Apache A

Re: Apache Arrow at JupyterCon

Thank you for sharing the videos. We are very interested in how to support Arrow data format and collection very closely, could you please help to point out which interfaces to allow Mnemonic act as a memory provider for the user to store and access Arrow managed datasets ? Thanks! Very truly your

[jira] [Created] (ARROW-1437) pa.Array.from_pandas segfaults when given a mixed-type array

Dima Ryazanov created ARROW-1437: Summary: pa.Array.from_pandas segfaults when given a mixed-type array Key: ARROW-1437 URL: https://issues.apache.org/jira/browse/ARROW-1437 Project: Apache Arrow

Re: Apache Arrow at JupyterCon

Great presentation! Thank you for sharing. On Thu, 31 Aug 2017 at 8:02 AM, Wes McKinney wrote: > Absolutely. I will do that now > > On Wed, Aug 30, 2017 at 3:33 PM, Julian Hyde wrote: > > Thanks for sharing. Can we tweet those videos as well? I see that > https://twitter.com/apachearrow

Re: Apache Arrow at JupyterCon

Absolutely. I will do that now On Wed, Aug 30, 2017 at 3:33 PM, Julian Hyde wrote: > Thanks for sharing. Can we tweet those videos as well? I see that > https://twitter.com/apachearrow only > tweeted your slides. > >> On Aug 26, 2017, at 1:11 PM, Wes McKinney

[jira] [Created] (ARROW-1436) PyArrow Timestamps written to Parquet as INT96 appear in Spark as 'bigint'

Lucas Pickup created ARROW-1436: --- Summary: PyArrow Timestamps written to Parquet as INT96 appear in Spark as 'bigint' Key: ARROW-1436 URL: https://issues.apache.org/jira/browse/ARROW-1436 Project: Apach

[jira] [Created] (ARROW-1435) PyArrow not propagating timezone information from Parquet to Pyhon

Lucas Pickup created ARROW-1435: --- Summary: PyArrow not propagating timezone information from Parquet to Pyhon Key: ARROW-1435 URL: https://issues.apache.org/jira/browse/ARROW-1435 Project: Apache Arrow

Re: Apache Arrow at JupyterCon

Thanks for sharing. Can we tweet those videos as well? I see that https://twitter.com/apachearrow only tweeted your slides. > On Aug 26, 2017, at 1:11 PM, Wes McKinney wrote: > > hi all, > > In case folks here are interested, I gave a keynote this week at > J

Re: PyArrow not retaining Parquet metadata

hi Lucas, Can you open a JIRA with this information on https://issues.apache.org/jira so we can investigate and resolve there in case a patch is required? No need to post a reply-to e-mail address -- development discussions should stay on public channels like the mailing list or JIRA. Thanks Wes

RE: PyArrow not retaining Parquet metadata

Please reply to: lucas.pic...@microsoft.com Outlook isn't playing nice. Apologies, Lucas Pickup -Original Message- From: Lucas Pickup [mailto:lucas.pic...@microsoft.com.INVALID] Sent: Wednesday, August 30, 2017 10:47 AM To: dev@arrow.apache.org Subject: PyArrow not retaining Parquet meta

PyArrow not retaining Parquet metadata

Hi All, I've encounter an issue where PyArrow does not appear to be propagating datetime metadata from parquet files into the resuling python objects. λ python Python 3.5.2 |Continuum Analytics, Inc.| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32 Type "help", "copyright"

[jira] [Created] (ARROW-1434) [C++/Python] pyarrow.Array.from_pandas does not support datetime64[D] arrays

Uwe L. Korn created ARROW-1434: -- Summary: [C++/Python] pyarrow.Array.from_pandas does not support datetime64[D] arrays Key: ARROW-1434 URL: https://issues.apache.org/jira/browse/ARROW-1434 Project: Apach

how to use arrow in project?

I want to use Arrow as a middle layer between spark and parquet data in HDFS, but I don't find any docs about how to load parquet data to arrow in memory, and how spark read arrow data format. Does anyone provide some examples or manuals to describe it? thanks.