[jira] [Commented] (ARROW-2713) [Packaging] Fix linux package builds
[ https://issues.apache.org/jira/browse/ARROW-2713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519868#comment-16519868 ] Kouhei Sutou commented on ARROW-2713: - The pull request have been merged. Can you rebase on master? > [Packaging] Fix linux package builds > > > Key: ARROW-2713 > URL: https://issues.apache.org/jira/browse/ARROW-2713 > Project: Apache Arrow > Issue Type: Improvement > Components: Packaging >Reporter: Krisztian Szucs >Priority: Major > Fix For: 0.10.0 > > > Build configuration: > https://github.com/kszucs/arrow/tree/0d9d89b7bff32823ab68e6ec1dc7ade52511f7ee/dev/tasks/linux-packages > Failing build: > https://travis-ci.org/kszucs/crossbow/builds/391894564?utm_source=github_status_medium=notification > Looks like it’s waiting for a user input? There might be some hardcoded > version too, because the expected is 0.9.1 instead of 0.9.0. > ping [~kou] -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (ARROW-2727) [Java] Unable to build java/adapters module
[
https://issues.apache.org/jira/browse/ARROW-2727?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Li Jin updated ARROW-2727:
--
Summary: [Java] Unable to build java/adapters module (was: [Java] Unable
to build java module)
> [Java] Unable to build java/adapters module
> ---
>
> Key: ARROW-2727
> URL: https://issues.apache.org/jira/browse/ARROW-2727
> Project: Apache Arrow
> Issue Type: Bug
>Reporter: Jeff Zhang
>Priority: Major
> Labels: pull-request-available
> Time Spent: 20m
> Remaining Estimate: 0h
>
> Due to pom issue.
> {code}
> Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=1024M;
> support was removed in 8.0
> [INFO] Scanning for projects...
> [ERROR] [ERROR] Some problems were encountered while processing the POMs:
> [FATAL] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13
> @
> [ERROR] The build could not read 1 project -> [Help 1]
> [ERROR]
> [ERROR] The project org.apache.arrow:arrow-jdbc:[unknown-version]
> (/Users/jzhang/github/arrow/java/adapter/jdbc/pom.xml) has 1 error
> [ERROR] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13 -> [Help
> 2]
> [ERROR]
> [ERROR] To see the full stack trace of the errors, re-run Maven with the -e
> switch.
> [ERROR] Re-run Maven using the -X switch to enable full debug logging.
> [ERROR]
> [ERROR] For more information about the errors and possible solutions, please
> read the following articles:
> [ERROR] [Help 1]
> http://cwiki.apache.org/confluence/display/MAVEN/ProjectBuildingException
> [ERROR] [Help 2]
> http://cwiki.apache.org/confluence/display/MAVEN/UnresolvableModelException
> ➜ arrow/java master ✓
> {code}
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[jira] [Updated] (ARROW-2727) [Java] Unable to build java module
[
https://issues.apache.org/jira/browse/ARROW-2727?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Li Jin updated ARROW-2727:
--
Summary: [Java] Unable to build java module (was: Unable to build java
module)
> [Java] Unable to build java module
> --
>
> Key: ARROW-2727
> URL: https://issues.apache.org/jira/browse/ARROW-2727
> Project: Apache Arrow
> Issue Type: Bug
>Reporter: Jeff Zhang
>Priority: Major
> Labels: pull-request-available
> Time Spent: 20m
> Remaining Estimate: 0h
>
> Due to pom issue.
> {code}
> Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=1024M;
> support was removed in 8.0
> [INFO] Scanning for projects...
> [ERROR] [ERROR] Some problems were encountered while processing the POMs:
> [FATAL] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13
> @
> [ERROR] The build could not read 1 project -> [Help 1]
> [ERROR]
> [ERROR] The project org.apache.arrow:arrow-jdbc:[unknown-version]
> (/Users/jzhang/github/arrow/java/adapter/jdbc/pom.xml) has 1 error
> [ERROR] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13 -> [Help
> 2]
> [ERROR]
> [ERROR] To see the full stack trace of the errors, re-run Maven with the -e
> switch.
> [ERROR] Re-run Maven using the -X switch to enable full debug logging.
> [ERROR]
> [ERROR] For more information about the errors and possible solutions, please
> read the following articles:
> [ERROR] [Help 1]
> http://cwiki.apache.org/confluence/display/MAVEN/ProjectBuildingException
> [ERROR] [Help 2]
> http://cwiki.apache.org/confluence/display/MAVEN/UnresolvableModelException
> ➜ arrow/java master ✓
> {code}
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[jira] [Updated] (ARROW-2729) [GLib] Add decimal128 array builder
[ https://issues.apache.org/jira/browse/ARROW-2729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] ASF GitHub Bot updated ARROW-2729: -- Labels: pull-request-available (was: ) > [GLib] Add decimal128 array builder > --- > > Key: ARROW-2729 > URL: https://issues.apache.org/jira/browse/ARROW-2729 > Project: Apache Arrow > Issue Type: New Feature > Components: GLib >Reporter: yosuke shiro >Assignee: yosuke shiro >Priority: Major > Labels: pull-request-available > > Support Decimal128Array and DecimalType. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (ARROW-2729) [GLib] Add decimal128 array builder
yosuke shiro created ARROW-2729: --- Summary: [GLib] Add decimal128 array builder Key: ARROW-2729 URL: https://issues.apache.org/jira/browse/ARROW-2729 Project: Apache Arrow Issue Type: New Feature Components: GLib Reporter: yosuke shiro Support Decimal128Array and DecimalType. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (ARROW-2729) [GLib] Add decimal128 array builder
[ https://issues.apache.org/jira/browse/ARROW-2729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] yosuke shiro reassigned ARROW-2729: --- Assignee: yosuke shiro > [GLib] Add decimal128 array builder > --- > > Key: ARROW-2729 > URL: https://issues.apache.org/jira/browse/ARROW-2729 > Project: Apache Arrow > Issue Type: New Feature > Components: GLib >Reporter: yosuke shiro >Assignee: yosuke shiro >Priority: Major > > Support Decimal128Array and DecimalType. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (ARROW-2728) [Python] Support partitioned Parquet datasets using glob-style file paths
[ https://issues.apache.org/jira/browse/ARROW-2728?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wes McKinney updated ARROW-2728: Summary: [Python] Support partitioned Parquet datasets using glob-style file paths (was: Pyarrow not adding partition columns when given a glob path) > [Python] Support partitioned Parquet datasets using glob-style file paths > - > > Key: ARROW-2728 > URL: https://issues.apache.org/jira/browse/ARROW-2728 > Project: Apache Arrow > Issue Type: Bug > Components: Python >Affects Versions: 0.9.0 > Environment: pyarrow : 0.9.0.post1 > dask : 0.17.1 > Mac OS >Reporter: pranav kohli >Priority: Minor > Labels: newbie > > I am saving a dask dataframe to parquet with two partition columns using the > pyarrow engine. The problem arises in scanning the partition columns. When I > scan using the directory path, I get the partition columns in the output > dataframe, whereas if I scan using the glob path, I dont get these columns > > https://github.com/apache/arrow/issues/2147 -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (ARROW-2720) [C++] Clean up cmake CXX_STANDARD and PIC flag setting
[
https://issues.apache.org/jira/browse/ARROW-2720?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wes McKinney updated ARROW-2720:
Fix Version/s: 0.10.0
> [C++] Clean up cmake CXX_STANDARD and PIC flag setting
> --
>
> Key: ARROW-2720
> URL: https://issues.apache.org/jira/browse/ARROW-2720
> Project: Apache Arrow
> Issue Type: Task
> Components: C++
>Reporter: Phillip Cloud
>Assignee: Phillip Cloud
>Priority: Major
> Fix For: 0.10.0
>
>
> We're using {{-std=c++11}} in a few non-external project places as well as
> setting {{-fPIC}}. CMake provides the {{CMAKE_CXX_STANDARD}} flag (which we
> are also using) and the {{CMAKE_POSITION_INDEPENDENT_CODE}} flag for setting
> these options in a cross platform way (where it matters).
> We should use these flags instead of using platform conditional checks to set
> their values explicitly.
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[jira] [Commented] (ARROW-2728) [Python] Support partitioned Parquet datasets using glob-style file paths
[ https://issues.apache.org/jira/browse/ARROW-2728?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519230#comment-16519230 ] Wes McKinney commented on ARROW-2728: - I renamed the issue slightly. Is there a formal specification for this or any other documentation, or is this an invention of the fastparquet project? > [Python] Support partitioned Parquet datasets using glob-style file paths > - > > Key: ARROW-2728 > URL: https://issues.apache.org/jira/browse/ARROW-2728 > Project: Apache Arrow > Issue Type: Bug > Components: Python >Affects Versions: 0.9.0 > Environment: pyarrow : 0.9.0.post1 > dask : 0.17.1 > Mac OS >Reporter: pranav kohli >Priority: Minor > Labels: newbie > > I am saving a dask dataframe to parquet with two partition columns using the > pyarrow engine. The problem arises in scanning the partition columns. When I > scan using the directory path, I get the partition columns in the output > dataframe, whereas if I scan using the glob path, I dont get these columns > > https://github.com/apache/arrow/issues/2147 -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (ARROW-2728) Pyarrow not adding partition columns when given a glob path
[ https://issues.apache.org/jira/browse/ARROW-2728?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] pranav kohli updated ARROW-2728: Description: I am saving a dask dataframe to parquet with two partition columns using the pyarrow engine. The problem arises in scanning the partition columns. When I scan using the directory path, I get the partition columns in the output dataframe, whereas if I scan using the glob path, I dont get these columns https://github.com/apache/arrow/issues/2147 was: I am saving a dask dataframe to parquet with two partition columns using the pyarrow engine. The problem arises in scanning the partition columns. When I scan using the directory path, I get the partition columns in the output dataframe, whereas if I scan using the glob path, I dont get these columns > Pyarrow not adding partition columns when given a glob path > --- > > Key: ARROW-2728 > URL: https://issues.apache.org/jira/browse/ARROW-2728 > Project: Apache Arrow > Issue Type: Bug > Components: Python >Affects Versions: 0.9.0 > Environment: pyarrow : 0.9.0.post1 > dask : 0.17.1 > Mac OS >Reporter: pranav kohli >Priority: Minor > Labels: newbie > > I am saving a dask dataframe to parquet with two partition columns using the > pyarrow engine. The problem arises in scanning the partition columns. When I > scan using the directory path, I get the partition columns in the output > dataframe, whereas if I scan using the glob path, I dont get these columns > > https://github.com/apache/arrow/issues/2147 -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (ARROW-2728) Pyarrow not adding partition columns when given a glob path
[ https://issues.apache.org/jira/browse/ARROW-2728?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] pranav kohli updated ARROW-2728: Description: I am saving a dask dataframe to parquet with two partition columns using the pyarrow engine. The problem arises in scanning the partition columns. When I scan using the directory path, I get the partition columns in the output dataframe, whereas if I scan using the glob path, I dont get these columns was:I am saving a dask dataframe to parquet with two partition columns using the pyarrow engine. The problem arises in scanning the partition columns. When I scan using the directory path, I get the partition columns in the output dataframe, whereas if I scan using the glob path, I dont get these columns > Pyarrow not adding partition columns when given a glob path > --- > > Key: ARROW-2728 > URL: https://issues.apache.org/jira/browse/ARROW-2728 > Project: Apache Arrow > Issue Type: Bug > Components: Python >Affects Versions: 0.9.0 > Environment: pyarrow : 0.9.0.post1 > dask : 0.17.1 > Mac OS >Reporter: pranav kohli >Priority: Minor > Labels: newbie > > I am saving a dask dataframe to parquet with two partition columns using the > pyarrow engine. The problem arises in scanning the partition columns. When I > scan using the directory path, I get the partition columns in the output > dataframe, whereas if I scan using the glob path, I dont get these columns > -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (ARROW-2720) [C++] Clean up cmake CXX_STANDARD and PIC flag setting
[
https://issues.apache.org/jira/browse/ARROW-2720?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519228#comment-16519228
]
Wes McKinney commented on ARROW-2720:
-
Definitely would be good to use the CMAKE_* stuff where we have control over
it. We'll still have to pass -fPIC to some of the external projects, but we
could handle that in {{ThirdpartyToolchain.cmake}}
> [C++] Clean up cmake CXX_STANDARD and PIC flag setting
> --
>
> Key: ARROW-2720
> URL: https://issues.apache.org/jira/browse/ARROW-2720
> Project: Apache Arrow
> Issue Type: Task
> Components: C++
>Reporter: Phillip Cloud
>Assignee: Phillip Cloud
>Priority: Major
> Fix For: 0.10.0
>
>
> We're using {{-std=c++11}} in a few non-external project places as well as
> setting {{-fPIC}}. CMake provides the {{CMAKE_CXX_STANDARD}} flag (which we
> are also using) and the {{CMAKE_POSITION_INDEPENDENT_CODE}} flag for setting
> these options in a cross platform way (where it matters).
> We should use these flags instead of using platform conditional checks to set
> their values explicitly.
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[jira] [Created] (ARROW-2728) Pyarrow not adding partition columns when given a glob path
pranav kohli created ARROW-2728: --- Summary: Pyarrow not adding partition columns when given a glob path Key: ARROW-2728 URL: https://issues.apache.org/jira/browse/ARROW-2728 Project: Apache Arrow Issue Type: Bug Components: Python Affects Versions: 0.9.0 Environment: pyarrow : 0.9.0.post1 dask : 0.17.1 Mac OS Reporter: pranav kohli I am saving a dask dataframe to parquet with two partition columns using the pyarrow engine. The problem arises in scanning the partition columns. When I scan using the directory path, I get the partition columns in the output dataframe, whereas if I scan using the glob path, I dont get these columns -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (ARROW-2722) [Python] ndarray to arrow conversion fails when downcasted from pandas to_numeric
[
https://issues.apache.org/jira/browse/ARROW-2722?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519197#comment-16519197
]
Wes McKinney commented on ARROW-2722:
-
Looks like a classic ULONGLONG/UINT64 issue.
> [Python] ndarray to arrow conversion fails when downcasted from pandas
> to_numeric
> -
>
> Key: ARROW-2722
> URL: https://issues.apache.org/jira/browse/ARROW-2722
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++, Python
>Affects Versions: 0.9.0
> Environment: Windows 10 64-bit
>Reporter: Augusto Radtke
>Priority: Major
> Fix For: 0.10.0
>
>
> The following snippet:
> {code:java}
> import numpy as np
> import pandas as pd
> import pyarrow as pa
> pa.array(pd.to_numeric(pd.Series(np.array([65536,2,3], dtype=np.uint64)),
> downcast='unsigned'),
> from_pandas=True, type='uint32')
> {code}
> fails to convert with message:
> {noformat}
> ArrowNotImplementedError Traceback (most recent call last)
> in ()
> 4
> 5 pa.array(pd.to_numeric(pd.Series(np.array([65536,2,3], dtype=np.uint64)),
> downcast='unsigned'),
> > 6 from_pandas=True, type='uint32')
> array.pxi in pyarrow.lib.array()
> array.pxi in pyarrow.lib._ndarray_to_array()
> error.pxi in pyarrow.lib.check_status()
> ArrowNotImplementedError: Unsupported numpy type 6{noformat}
>
> This is a Windows 64-bit machine, running Python 3.6.5, pyarrow 0.9.0, pandas
> 0.23.1 and numpy 1.14.5.
> Seems to be fine for uint16 or uint8 downcasting. Unfortunately I didn't had
> the time to dig deeper or try on a Linux machine but it feels like its
> related to the LLP64 model.
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[jira] [Updated] (ARROW-2722) [Python] ndarray to arrow conversion fails when downcasted from pandas to_numeric
[
https://issues.apache.org/jira/browse/ARROW-2722?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wes McKinney updated ARROW-2722:
Summary: [Python] ndarray to arrow conversion fails when downcasted from
pandas to_numeric (was: ndarray to arrow conversion fails when downcasted from
pandas to_numeric)
> [Python] ndarray to arrow conversion fails when downcasted from pandas
> to_numeric
> -
>
> Key: ARROW-2722
> URL: https://issues.apache.org/jira/browse/ARROW-2722
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++, Python
>Affects Versions: 0.9.0
> Environment: Windows 10 64-bit
>Reporter: Augusto Radtke
>Priority: Major
>
> The following snippet:
> {code:java}
> import numpy as np
> import pandas as pd
> import pyarrow as pa
> pa.array(pd.to_numeric(pd.Series(np.array([65536,2,3], dtype=np.uint64)),
> downcast='unsigned'),
> from_pandas=True, type='uint32')
> {code}
> fails to convert with message:
> {noformat}
> ArrowNotImplementedError Traceback (most recent call last)
> in ()
> 4
> 5 pa.array(pd.to_numeric(pd.Series(np.array([65536,2,3], dtype=np.uint64)),
> downcast='unsigned'),
> > 6 from_pandas=True, type='uint32')
> array.pxi in pyarrow.lib.array()
> array.pxi in pyarrow.lib._ndarray_to_array()
> error.pxi in pyarrow.lib.check_status()
> ArrowNotImplementedError: Unsupported numpy type 6{noformat}
>
> This is a Windows 64-bit machine, running Python 3.6.5, pyarrow 0.9.0, pandas
> 0.23.1 and numpy 1.14.5.
> Seems to be fine for uint16 or uint8 downcasting. Unfortunately I didn't had
> the time to dig deeper or try on a Linux machine but it feels like its
> related to the LLP64 model.
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[jira] [Commented] (ARROW-2714) [C++/Python] Variable step size slicing for arrays
[
https://issues.apache.org/jira/browse/ARROW-2714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519174#comment-16519174
]
Wes McKinney commented on ARROW-2714:
-
The Tensor classes are independent from the columnar data structures, though
they reuse pieces of metadata, metadata serialization, memory management, and
IPC.
The purpose of adding these to the library was to have in-memory data
structures for handling Tensor/ndarray data and metadata that "plug in" to the
rest of the Arrow C++ system (Plasma store, IO subsystem, memory pools,
buffers, etc.).
Theoretically you could return a Tensor when creating a non-contiguous slice of
an Array; in light of the above, I don't think that would be intuitive.
When we started the project, our focus was creating an open standard for
in-memory columnar data, a hitherto unsolved problem. The project's scope has
expanded into peripheral problems in the same domain in the meantime (with the
mantra of creating interoperable components, a use-what-you-need development
platform for system developers). I think this aspect of the project could be
better documented / advertised, since the project's initial focus on the
columnar standard has given some the mistaken impression that we are not
interested in any work outside of that.
> [C++/Python] Variable step size slicing for arrays
> --
>
> Key: ARROW-2714
> URL: https://issues.apache.org/jira/browse/ARROW-2714
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
>Reporter: Florian Jetter
>Priority: Minor
>
> Array slicing should support variable step sizes
> The current behavior raises an {{IndexError}}, e.g.
> {code}
> In [8]: import pyarrow as pa
> In [9]: pa.array([1, 2, 3])[::-1]
> ---
> IndexError Traceback (most recent call last)
> in ()
> > 1 pa.array([1, 2, 3])[::-1]
> array.pxi in pyarrow.lib.Array.__getitem__()
> array.pxi in pyarrow.lib._normalize_slice()
> IndexError: only slices with step 1 supported
> {code}
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[jira] [Commented] (ARROW-2714) [C++/Python] Variable step size slicing for arrays
[
https://issues.apache.org/jira/browse/ARROW-2714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519136#comment-16519136
]
Antoine Pitrou commented on ARROW-2714:
---
Yes... but then our arrays would do zero-copy slices in some cases and not in
other cases. So it's confusing (and can hide bugs).
+1 for an explicit reversal function / kernel.
(also, what's the status of the Tensor API? it does have a strides)
> [C++/Python] Variable step size slicing for arrays
> --
>
> Key: ARROW-2714
> URL: https://issues.apache.org/jira/browse/ARROW-2714
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
>Reporter: Florian Jetter
>Priority: Minor
>
> Array slicing should support variable step sizes
> The current behavior raises an {{IndexError}}, e.g.
> {code}
> In [8]: import pyarrow as pa
> In [9]: pa.array([1, 2, 3])[::-1]
> ---
> IndexError Traceback (most recent call last)
> in ()
> > 1 pa.array([1, 2, 3])[::-1]
> array.pxi in pyarrow.lib.Array.__getitem__()
> array.pxi in pyarrow.lib._normalize_slice()
> IndexError: only slices with step 1 supported
> {code}
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[jira] [Commented] (ARROW-2714) [C++/Python] Variable step size slicing for arrays
[
https://issues.apache.org/jira/browse/ARROW-2714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519130#comment-16519130
]
Wes McKinney commented on ARROW-2714:
-
Only if they're using NumPy, though. With Python lists it's a copy, right? I
don't think we should burden ourselves by inheriting too many semantics from
NumPy.
Personally I would rather have an explicit {{reverse}} function to do
{{[::-1]}} and continue to disallow slicing with any step but 1
> [C++/Python] Variable step size slicing for arrays
> --
>
> Key: ARROW-2714
> URL: https://issues.apache.org/jira/browse/ARROW-2714
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
>Reporter: Florian Jetter
>Priority: Minor
>
> Array slicing should support variable step sizes
> The current behavior raises an {{IndexError}}, e.g.
> {code}
> In [8]: import pyarrow as pa
> In [9]: pa.array([1, 2, 3])[::-1]
> ---
> IndexError Traceback (most recent call last)
> in ()
> > 1 pa.array([1, 2, 3])[::-1]
> array.pxi in pyarrow.lib.Array.__getitem__()
> array.pxi in pyarrow.lib._normalize_slice()
> IndexError: only slices with step 1 supported
> {code}
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[jira] [Commented] (ARROW-2714) [C++/Python] Variable step size slicing for arrays
[
https://issues.apache.org/jira/browse/ARROW-2714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519126#comment-16519126
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Antoine Pitrou commented on ARROW-2714:
---
Hmm, then I think it can be counter-intuitive for users (who would generally
expect slices to be zero-copy views, but suddently get a copy with a non-unit
step).
> [C++/Python] Variable step size slicing for arrays
> --
>
> Key: ARROW-2714
> URL: https://issues.apache.org/jira/browse/ARROW-2714
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
>Reporter: Florian Jetter
>Priority: Minor
>
> Array slicing should support variable step sizes
> The current behavior raises an {{IndexError}}, e.g.
> {code}
> In [8]: import pyarrow as pa
> In [9]: pa.array([1, 2, 3])[::-1]
> ---
> IndexError Traceback (most recent call last)
> in ()
> > 1 pa.array([1, 2, 3])[::-1]
> array.pxi in pyarrow.lib.Array.__getitem__()
> array.pxi in pyarrow.lib._normalize_slice()
> IndexError: only slices with step 1 supported
> {code}
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[jira] [Commented] (ARROW-2714) [C++/Python] Variable step size slicing for arrays
[
https://issues.apache.org/jira/browse/ARROW-2714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519123#comment-16519123
]
Wes McKinney commented on ARROW-2714:
-
The only option would be to produce a copy. That makes this a somewhat complex
task (writing a new computational kernel, in essence)
> [C++/Python] Variable step size slicing for arrays
> --
>
> Key: ARROW-2714
> URL: https://issues.apache.org/jira/browse/ARROW-2714
> Project: Apache Arrow
> Issue Type: New Feature
> Components: C++, Python
>Reporter: Florian Jetter
>Priority: Minor
>
> Array slicing should support variable step sizes
> The current behavior raises an {{IndexError}}, e.g.
> {code}
> In [8]: import pyarrow as pa
> In [9]: pa.array([1, 2, 3])[::-1]
> ---
> IndexError Traceback (most recent call last)
> in ()
> > 1 pa.array([1, 2, 3])[::-1]
> array.pxi in pyarrow.lib.Array.__getitem__()
> array.pxi in pyarrow.lib._normalize_slice()
> IndexError: only slices with step 1 supported
> {code}
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[jira] [Resolved] (ARROW-2726) [C++] The latest Boost version is wrong
[ https://issues.apache.org/jira/browse/ARROW-2726?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wes McKinney resolved ARROW-2726. - Resolution: Fixed Fix Version/s: 0.10.0 Issue resolved by pull request 2150 [https://github.com/apache/arrow/pull/2150] > [C++] The latest Boost version is wrong > --- > > Key: ARROW-2726 > URL: https://issues.apache.org/jira/browse/ARROW-2726 > Project: Apache Arrow > Issue Type: Bug > Components: C++ >Reporter: Kouhei Sutou >Assignee: Kouhei Sutou >Priority: Minor > Labels: pull-request-available > Fix For: 0.10.0 > > Time Spent: 40m > Remaining Estimate: 0h > > Boost 1.68.0 isn't released yet. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (ARROW-2727) Unable to build java module
[
https://issues.apache.org/jira/browse/ARROW-2727?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated ARROW-2727:
--
Labels: pull-request-available (was: )
> Unable to build java module
> ---
>
> Key: ARROW-2727
> URL: https://issues.apache.org/jira/browse/ARROW-2727
> Project: Apache Arrow
> Issue Type: Bug
>Reporter: Jeff Zhang
>Priority: Major
> Labels: pull-request-available
>
> Due to pom issue.
> {code}
> Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=1024M;
> support was removed in 8.0
> [INFO] Scanning for projects...
> [ERROR] [ERROR] Some problems were encountered while processing the POMs:
> [FATAL] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13
> @
> [ERROR] The build could not read 1 project -> [Help 1]
> [ERROR]
> [ERROR] The project org.apache.arrow:arrow-jdbc:[unknown-version]
> (/Users/jzhang/github/arrow/java/adapter/jdbc/pom.xml) has 1 error
> [ERROR] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13 -> [Help
> 2]
> [ERROR]
> [ERROR] To see the full stack trace of the errors, re-run Maven with the -e
> switch.
> [ERROR] Re-run Maven using the -X switch to enable full debug logging.
> [ERROR]
> [ERROR] For more information about the errors and possible solutions, please
> read the following articles:
> [ERROR] [Help 1]
> http://cwiki.apache.org/confluence/display/MAVEN/ProjectBuildingException
> [ERROR] [Help 2]
> http://cwiki.apache.org/confluence/display/MAVEN/UnresolvableModelException
> ➜ arrow/java master ✓
> {code}
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[jira] [Updated] (ARROW-2727) Unable to build java module
[
https://issues.apache.org/jira/browse/ARROW-2727?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jeff Zhang updated ARROW-2727:
--
Description:
Due to pom issue.
{code}
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=1024M;
support was removed in 8.0
[INFO] Scanning for projects...
[ERROR] [ERROR] Some problems were encountered while processing the POMs:
[FATAL] Non-resolvable parent POM for
org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and 'parent.relativePath'
points at wrong local POM @ line 16, column 13
@
[ERROR] The build could not read 1 project -> [Help 1]
[ERROR]
[ERROR] The project org.apache.arrow:arrow-jdbc:[unknown-version]
(/Users/jzhang/github/arrow/java/adapter/jdbc/pom.xml) has 1 error
[ERROR] Non-resolvable parent POM for
org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and 'parent.relativePath'
points at wrong local POM @ line 16, column 13 -> [Help 2]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e
switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please
read the following articles:
[ERROR] [Help 1]
http://cwiki.apache.org/confluence/display/MAVEN/ProjectBuildingException
[ERROR] [Help 2]
http://cwiki.apache.org/confluence/display/MAVEN/UnresolvableModelException
➜ arrow/java master ✓
{code}
was:
Due to pom issue.
{code}
{code}
> Unable to build java module
> ---
>
> Key: ARROW-2727
> URL: https://issues.apache.org/jira/browse/ARROW-2727
> Project: Apache Arrow
> Issue Type: Bug
>Reporter: Jeff Zhang
>Priority: Major
>
> Due to pom issue.
> {code}
> Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=1024M;
> support was removed in 8.0
> [INFO] Scanning for projects...
> [ERROR] [ERROR] Some problems were encountered while processing the POMs:
> [FATAL] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13
> @
> [ERROR] The build could not read 1 project -> [Help 1]
> [ERROR]
> [ERROR] The project org.apache.arrow:arrow-jdbc:[unknown-version]
> (/Users/jzhang/github/arrow/java/adapter/jdbc/pom.xml) has 1 error
> [ERROR] Non-resolvable parent POM for
> org.apache.arrow:arrow-jdbc:[unknown-version]: Could not find artifact
> org.apache.arrow:arrow-java-root:pom:0.10.0-SNAPSHOT and
> 'parent.relativePath' points at wrong local POM @ line 16, column 13 -> [Help
> 2]
> [ERROR]
> [ERROR] To see the full stack trace of the errors, re-run Maven with the -e
> switch.
> [ERROR] Re-run Maven using the -X switch to enable full debug logging.
> [ERROR]
> [ERROR] For more information about the errors and possible solutions, please
> read the following articles:
> [ERROR] [Help 1]
> http://cwiki.apache.org/confluence/display/MAVEN/ProjectBuildingException
> [ERROR] [Help 2]
> http://cwiki.apache.org/confluence/display/MAVEN/UnresolvableModelException
> ➜ arrow/java master ✓
> {code}
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[jira] [Updated] (ARROW-2727) Unable to build java module
[
https://issues.apache.org/jira/browse/ARROW-2727?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jeff Zhang updated ARROW-2727:
--
Issue Type: Bug (was: Improvement)
> Unable to build java module
> ---
>
> Key: ARROW-2727
> URL: https://issues.apache.org/jira/browse/ARROW-2727
> Project: Apache Arrow
> Issue Type: Bug
>Reporter: Jeff Zhang
>Priority: Major
>
> Due to pom issue.
> {code}
> {code}
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[jira] [Created] (ARROW-2727) Unable to build java module
Jeff Zhang created ARROW-2727:
-
Summary: Unable to build java module
Key: ARROW-2727
URL: https://issues.apache.org/jira/browse/ARROW-2727
Project: Apache Arrow
Issue Type: Improvement
Reporter: Jeff Zhang
Due to pom issue.
{code}
{code}
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