[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Stamatis Zampetakis updated HIVE-19256:
---
Fix Version/s: (was: 3.2.0)
I cleared the fixVersion field since this ticket is not resolved. Please review
this ticket and if the fix is already committed to a specific version please
set the version accordingly and mark the ticket as RESOLVED.
According to the JIRA guidelines
(https://cwiki.apache.org/confluence/display/Hive/HowToContribute) the
fixVersion should be set only when the issue is resolved/closed.
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
> Components: Hive
>Affects Versions: 3.1.0
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch, HIVE-19256_1.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Vineet Garg updated HIVE-19256:
---
Fix Version/s: (was: 3.1.0)
3.2.0
Deferring this to 3.2.0 since the branch for 3.1.0 has been cut off.
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
> Components: Hive
>Affects Versions: 3.1.0
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Fix For: 3.2.0
>
> Attachments: HIVE-19256.patch, HIVE-19256_1.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Affects Version/s: 3.1.0
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
> Components: Hive
>Affects Versions: 3.1.0
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Fix For: 3.1.0
>
> Attachments: HIVE-19256.patch, HIVE-19256_1.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Fix Version/s: 3.1.0
Component/s: Hive
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
> Components: Hive
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Fix For: 3.1.0
>
> Attachments: HIVE-19256.patch, HIVE-19256_1.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Attachment: HIVE-19256_1.patch
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch, HIVE-19256_1.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Status: Patch Available (was: Open)
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch, HIVE-19256_1.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Attachment: (was: generic_project.diff)
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Attachment: generic_project.diff
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch, generic_project.diff
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Attachment: (was: generic_project.diff)
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch, generic_project.diff
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Attachment: HIVE-19256.patch
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: HIVE-19256.patch, generic_project.diff
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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[jira] [Updated] (HIVE-19256) UDF which shapes the input data according to the specified schema
[
https://issues.apache.org/jira/browse/HIVE-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ratandeep Ratti updated HIVE-19256:
---
Attachment: generic_project.diff
> UDF which shapes the input data according to the specified schema
> -
>
> Key: HIVE-19256
> URL: https://issues.apache.org/jira/browse/HIVE-19256
> Project: Hive
> Issue Type: New Feature
>Reporter: Ratandeep Ratti
>Assignee: Ratandeep Ratti
>Priority: Major
> Attachments: generic_project.diff
>
>
> We use this UDF a lot in our org. This UDF takes an object and a Hive schema
> and make sure the output object matches the schema completely. In some
> respects it is similar to {{named
> _struct}} UDF which can be used to select columns from a struct, but it is
> more general since it can work not only on structs, but all Hive data types
> (expect union). Also the schema can provide certain valid type conversions
> (int -> double etc)
> One scenario where this is quite useful is making sure that the Hive view
> created with a specific schema will have columns which will always match that
> schema. In Hive today when a view is created, new nested columns from the
> underlying table can leak out from the view, even though the user never
> wanted this behavior. Note that this leaking of columns is only for nested
> columns and not for top level columns, so in that regard this behavior of
> Hive is inconsistent.
> Sample usage of the UDF
> {code}
> generic_project(col, "struct>>") // Returning
> data which matches the input schema. Here extra columns which are not part of
> the input will be removed
> generic_project(col, "struct") // If the input column had a struct
> with col a as int . It would type cast 'a' to double.
> {code}
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