[jira] [Updated] (SPARK-30762) Add dtype="float32" support to vector_to_array UDF
[
https://issues.apache.org/jira/browse/SPARK-30762?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Weichen Xu updated SPARK-30762:
---
Fix Version/s: 3.1.0
3.0.0
> Add dtype="float32" support to vector_to_array UDF
> --
>
> Key: SPARK-30762
> URL: https://issues.apache.org/jira/browse/SPARK-30762
> Project: Spark
> Issue Type: Story
> Components: MLlib, PySpark
>Affects Versions: 3.0.0
>Reporter: Liang Zhang
>Assignee: Liang Zhang
>Priority: Major
> Fix For: 3.0.0, 3.1.0
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Previous PR:
> [https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py]
> In the previous PR, we introduced a UDF to convert a column of MLlib Vecters
> to a column of lists in python (Seq in scala). Currently, all the floating
> numbers in a vector is converted to Double in scala. In this issue, we will
> add a parameter in the python function {{vector_to_array(col)}} that allows
> converting to Float (32bits) in scala, which would be mapped to a numpy array
> of dtype=float32.
>
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[jira] [Updated] (SPARK-30762) Add dtype="float32" support to vector_to_array UDF
[
https://issues.apache.org/jira/browse/SPARK-30762?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Weichen Xu updated SPARK-30762:
---
Fix Version/s: (was: 3.1.0)
(was: 3.0.0)
> Add dtype="float32" support to vector_to_array UDF
> --
>
> Key: SPARK-30762
> URL: https://issues.apache.org/jira/browse/SPARK-30762
> Project: Spark
> Issue Type: Story
> Components: MLlib, PySpark
>Affects Versions: 3.0.0
>Reporter: Liang Zhang
>Assignee: Liang Zhang
>Priority: Major
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Previous PR:
> [https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py]
> In the previous PR, we introduced a UDF to convert a column of MLlib Vecters
> to a column of lists in python (Seq in scala). Currently, all the floating
> numbers in a vector is converted to Double in scala. In this issue, we will
> add a parameter in the python function {{vector_to_array(col)}} that allows
> converting to Float (32bits) in scala, which would be mapped to a numpy array
> of dtype=float32.
>
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[jira] [Updated] (SPARK-30762) Add dtype="float32" support to vector_to_array UDF
[
https://issues.apache.org/jira/browse/SPARK-30762?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Weichen Xu updated SPARK-30762:
---
Fix Version/s: 3.1.0
3.0.0
> Add dtype="float32" support to vector_to_array UDF
> --
>
> Key: SPARK-30762
> URL: https://issues.apache.org/jira/browse/SPARK-30762
> Project: Spark
> Issue Type: Story
> Components: MLlib, PySpark
>Affects Versions: 3.0.0
>Reporter: Liang Zhang
>Assignee: Liang Zhang
>Priority: Major
> Fix For: 3.0.0, 3.1.0
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Previous PR:
> [https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py]
> In the previous PR, we introduced a UDF to convert a column of MLlib Vecters
> to a column of lists in python (Seq in scala). Currently, all the floating
> numbers in a vector is converted to Double in scala. In this issue, we will
> add a parameter in the python function {{vector_to_array(col)}} that allows
> converting to Float (32bits) in scala, which would be mapped to a numpy array
> of dtype=float32.
>
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[jira] [Updated] (SPARK-30762) Add dtype="float32" support to vector_to_array UDF
[
https://issues.apache.org/jira/browse/SPARK-30762?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Liang Zhang updated SPARK-30762:
Description:
Previous PR:
[https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py]
In the previous PR, we introduced a UDF to convert a column of MLlib Vecters to
a column of lists in python (Seq in scala). Currently, all the floating numbers
in a vector is converted to Double in scala. In this issue, we will add a
parameter in the python function {{vector_to_array(col)}} that allows
converting to Float (32bits) in scala, which would be mapped to a numpy array
of dtype=float32.
was:
Previous PR:
[https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py]
> Add dtype="float32" support to vector_to_array UDF
> --
>
> Key: SPARK-30762
> URL: https://issues.apache.org/jira/browse/SPARK-30762
> Project: Spark
> Issue Type: Story
> Components: MLlib, PySpark
>Affects Versions: 3.0.0
>Reporter: Liang Zhang
>Assignee: Liang Zhang
>Priority: Major
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Previous PR:
> [https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py]
> In the previous PR, we introduced a UDF to convert a column of MLlib Vecters
> to a column of lists in python (Seq in scala). Currently, all the floating
> numbers in a vector is converted to Double in scala. In this issue, we will
> add a parameter in the python function {{vector_to_array(col)}} that allows
> converting to Float (32bits) in scala, which would be mapped to a numpy array
> of dtype=float32.
>
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[jira] [Updated] (SPARK-30762) Add dtype="float32" support to vector_to_array UDF
[ https://issues.apache.org/jira/browse/SPARK-30762?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng updated SPARK-30762: -- Component/s: PySpark > Add dtype="float32" support to vector_to_array UDF > -- > > Key: SPARK-30762 > URL: https://issues.apache.org/jira/browse/SPARK-30762 > Project: Spark > Issue Type: Story > Components: MLlib, PySpark >Affects Versions: 3.0.0 >Reporter: Liang Zhang >Assignee: Liang Zhang >Priority: Major > Original Estimate: 24h > Remaining Estimate: 24h > > Previous PR: > [https://github.com/apache/spark/blob/master/python/pyspark/ml/functions.py] > > -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
