[jira] [Updated] (ARROW-11269) [Rust] Unable to read Parquet file because of mismatch in column-derived and embedded schemas
[
https://issues.apache.org/jira/browse/ARROW-11269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Andy Grove updated ARROW-11269:
---
Fix Version/s: 3.0.1
> [Rust] Unable to read Parquet file because of mismatch in column-derived and
> embedded schemas
> -
>
> Key: ARROW-11269
> URL: https://issues.apache.org/jira/browse/ARROW-11269
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust
>Affects Versions: 3.0.0
>Reporter: Max Burke
>Assignee: Neville Dipale
>Priority: Blocker
> Labels: pull-request-available
> Fix For: 4.0.0, 3.0.1
>
> Attachments: 0100c937-7c1c-78c4-1f4b-156ef04e79f0.parquet, main.rs
>
> Time Spent: 1h 50m
> Remaining Estimate: 0h
>
> The issue seems to stem from the new(-ish) behavior of the Arrow Parquet
> reader where the embedded arrow schema is used instead of deriving the schema
> from the Parquet columns.
>
> However it seems like some cases still derive the schema type from the column
> types, leading to the Arrow record batch reader erroring out that the column
> types must match the schema types.
>
> In our case, the column type is an int96 datetime (ns) type, and the Arrow
> type in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
> Some("UTC")). However, the code that constructs the Arrays seems to re-derive
> this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
> the Parquet schema has no timezone information). And so, Parquet files that
> we were able to read successfully with our branch of Arrow circa October are
> now unreadable.
>
> I've attached an example of a Parquet file that demonstrates the problem.
> This file was created in Python (as most of our Parquet files are).
>
> I've also attached a sample Rust program that will demonstrate the error.
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[jira] [Updated] (ARROW-11269) [Rust] Unable to read Parquet file because of mismatch in column-derived and embedded schemas
[
https://issues.apache.org/jira/browse/ARROW-11269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated ARROW-11269:
---
Labels: pull-request-available (was: )
> [Rust] Unable to read Parquet file because of mismatch in column-derived and
> embedded schemas
> -
>
> Key: ARROW-11269
> URL: https://issues.apache.org/jira/browse/ARROW-11269
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust
>Affects Versions: 3.0.0
>Reporter: Max Burke
>Priority: Blocker
> Labels: pull-request-available
> Attachments: 0100c937-7c1c-78c4-1f4b-156ef04e79f0.parquet, main.rs
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> The issue seems to stem from the new(-ish) behavior of the Arrow Parquet
> reader where the embedded arrow schema is used instead of deriving the schema
> from the Parquet columns.
>
> However it seems like some cases still derive the schema type from the column
> types, leading to the Arrow record batch reader erroring out that the column
> types must match the schema types.
>
> In our case, the column type is an int96 datetime (ns) type, and the Arrow
> type in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
> Some("UTC")). However, the code that constructs the Arrays seems to re-derive
> this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
> the Parquet schema has no timezone information). And so, Parquet files that
> we were able to read successfully with our branch of Arrow circa October are
> now unreadable.
>
> I've attached an example of a Parquet file that demonstrates the problem.
> This file was created in Python (as most of our Parquet files are).
>
> I've also attached a sample Rust program that will demonstrate the error.
--
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[jira] [Updated] (ARROW-11269) [Rust] Unable to read Parquet file because of mismatch in column-derived and embedded schemas
[
https://issues.apache.org/jira/browse/ARROW-11269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Max Burke updated ARROW-11269:
--
Description:
The issue seems to stem from the new(-ish) behavior of the Arrow Parquet reader
where the embedded arrow schema is used instead of deriving the schema from the
Parquet columns.
However it seems like some cases still derive the schema type from the column
types, leading to the Arrow record batch reader erroring out that the column
types must match the schema types.
In our case, the column type is an int96 datetime (ns) type, and the Arrow type
in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
Some("UTC")). However, the code that constructs the Arrays seems to re-derive
this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
the Parquet schema has no timezone information). And so, Parquet files that we
were able to read successfully with our branch of Arrow circa October are now
unreadable.
I've attached an example of a Parquet file that demonstrates the problem. This
file was created in Python (as most of our Parquet files are).
I've also attached a sample Rust program that will demonstrate the error.
was:
The issue seems to stem from the new(-ish) behavior of the Arrow Parquet reader
where the embedded arrow schema is used instead of deriving the schema from the
Parquet columns.
However it seems like some cases still derive the schema type from the column
types, leading to the Arrow record batch reader erroring out that the column
types must match the schema types.
In our case, the column type is an int96 datetime (ns) type, and the Arrow type
in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
Some("UTC")). However, the code that constructs the Arrays seems to re-derive
this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
the Parquet schema has no timezone information). And so, Parquet files that we
were able to read successfully with our branch of Arrow circa October are now
unreadable.
I've attached an example of a Parquet file that demonstrates the problem. This
file was created in Python (as most of our Parquet files are).
I've also attached a sample Rust program that will demonstrate the error.
> [Rust] Unable to read Parquet file because of mismatch in column-derived and
> embedded schemas
> -
>
> Key: ARROW-11269
> URL: https://issues.apache.org/jira/browse/ARROW-11269
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust
>Affects Versions: 3.0.0
>Reporter: Max Burke
>Priority: Blocker
> Attachments: 0100c937-7c1c-78c4-1f4b-156ef04e79f0.parquet, main.rs
>
>
> The issue seems to stem from the new(-ish) behavior of the Arrow Parquet
> reader where the embedded arrow schema is used instead of deriving the schema
> from the Parquet columns.
>
> However it seems like some cases still derive the schema type from the column
> types, leading to the Arrow record batch reader erroring out that the column
> types must match the schema types.
>
> In our case, the column type is an int96 datetime (ns) type, and the Arrow
> type in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
> Some("UTC")). However, the code that constructs the Arrays seems to re-derive
> this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
> the Parquet schema has no timezone information). And so, Parquet files that
> we were able to read successfully with our branch of Arrow circa October are
> now unreadable.
>
> I've attached an example of a Parquet file that demonstrates the problem.
> This file was created in Python (as most of our Parquet files are).
>
> I've also attached a sample Rust program that will demonstrate the error.
--
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[jira] [Updated] (ARROW-11269) [Rust] Unable to read Parquet file because of mismatch in column-derived and embedded schemas
[
https://issues.apache.org/jira/browse/ARROW-11269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Max Burke updated ARROW-11269:
--
Description:
The issue seems to stem from the new(-ish) behavior of the Arrow Parquet reader
where the embedded arrow schema is used instead of deriving the schema from the
Parquet columns.
However it seems like some cases still derive the schema type from the column
types, leading to the Arrow record batch reader erroring out that the column
types must match the schema types.
In our case, the column type is an int96 datetime (ns) type, and the Arrow type
in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
Some("UTC")). However, the code that constructs the Arrays seems to re-derive
this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
the Parquet schema has no timezone information). And so, Parquet files that we
were able to read successfully with our branch of Arrow circa October are now
unreadable.
I've attached an example of a Parquet file that demonstrates the problem. This
file was created in Python (as most of our Parquet files are).
I've also attached a sample Rust program that will demonstrate the error.
was:
The issue seems to stem from the new(-ish) behavior of the Arrow Parquet reader
where the embedded arrow schema is used instead of deriving the schema from the
Parquet columns.
However it seems like some cases still derive the schema type from the column
types, leading to the Arrow record batch reader erroring out that the column
types must match the schema types.
In our case, the column type is an int96 datetime (ns) type, and the Arrow type
in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
Some("UTC")). However, the code that constructs the Arrays seems to re-derive
this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
the Parquet schema has no timezone information). And so, Parquet files that we
were able to read successfully with our branch of Arrow circa October are now
unreadable.
I've attached an example of a Parquet file that demonstrates the problem. This
file was created in Python (as most of our Parquet files are).
> [Rust] Unable to read Parquet file because of mismatch in column-derived and
> embedded schemas
> -
>
> Key: ARROW-11269
> URL: https://issues.apache.org/jira/browse/ARROW-11269
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust
>Affects Versions: 3.0.0
>Reporter: Max Burke
>Priority: Blocker
> Attachments: 0100c937-7c1c-78c4-1f4b-156ef04e79f0.parquet, main.rs
>
>
> The issue seems to stem from the new(-ish) behavior of the Arrow Parquet
> reader where the embedded arrow schema is used instead of deriving the schema
> from the Parquet columns.
>
> However it seems like some cases still derive the schema type from the column
> types, leading to the Arrow record batch reader erroring out that the column
> types must match the schema types.
>
> In our case, the column type is an int96 datetime (ns) type, and the Arrow
> type in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
> Some("UTC")). However, the code that constructs the Arrays seems to re-derive
> this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
> the Parquet schema has no timezone information). And so, Parquet files that
> we were able to read successfully with our branch of Arrow circa October are
> now unreadable.
>
> I've attached an example of a Parquet file that demonstrates the problem.
> This file was created in Python (as most of our Parquet files are).
> I've also attached a sample Rust program that will demonstrate the error.
--
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[jira] [Updated] (ARROW-11269) [Rust] Unable to read Parquet file because of mismatch in column-derived and embedded schemas
[
https://issues.apache.org/jira/browse/ARROW-11269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Max Burke updated ARROW-11269:
--
Attachment: main.rs
> [Rust] Unable to read Parquet file because of mismatch in column-derived and
> embedded schemas
> -
>
> Key: ARROW-11269
> URL: https://issues.apache.org/jira/browse/ARROW-11269
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust
>Affects Versions: 3.0.0
>Reporter: Max Burke
>Priority: Blocker
> Attachments: 0100c937-7c1c-78c4-1f4b-156ef04e79f0.parquet, main.rs
>
>
> The issue seems to stem from the new(-ish) behavior of the Arrow Parquet
> reader where the embedded arrow schema is used instead of deriving the schema
> from the Parquet columns.
>
> However it seems like some cases still derive the schema type from the column
> types, leading to the Arrow record batch reader erroring out that the column
> types must match the schema types.
>
> In our case, the column type is an int96 datetime (ns) type, and the Arrow
> type in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
> Some("UTC")). However, the code that constructs the Arrays seems to re-derive
> this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
> the Parquet schema has no timezone information). And so, Parquet files that
> we were able to read successfully with our branch of Arrow circa October are
> now unreadable.
>
> I've attached an example of a Parquet file that demonstrates the problem.
> This file was created in Python (as most of our Parquet files are).
> I've also attached a sample Rust program that will demonstrate the error.
--
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[jira] [Updated] (ARROW-11269) [Rust] Unable to read Parquet file because of mismatch in column-derived and embedded schemas
[
https://issues.apache.org/jira/browse/ARROW-11269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Max Burke updated ARROW-11269:
--
Summary: [Rust] Unable to read Parquet file because of mismatch in
column-derived and embedded schemas (was: [Rust] Unable to read Parquet file
because of mismatch )
> [Rust] Unable to read Parquet file because of mismatch in column-derived and
> embedded schemas
> -
>
> Key: ARROW-11269
> URL: https://issues.apache.org/jira/browse/ARROW-11269
> Project: Apache Arrow
> Issue Type: Bug
> Components: Rust
>Affects Versions: 3.0.0
>Reporter: Max Burke
>Priority: Blocker
> Attachments: 0100c937-7c1c-78c4-1f4b-156ef04e79f0.parquet
>
>
> The issue seems to stem from the new(-ish) behavior of the Arrow Parquet
> reader where the embedded arrow schema is used instead of deriving the schema
> from the Parquet columns.
>
> However it seems like some cases still derive the schema type from the column
> types, leading to the Arrow record batch reader erroring out that the column
> types must match the schema types.
>
> In our case, the column type is an int96 datetime (ns) type, and the Arrow
> type in the embedded schema is DataType::Timestamp(TimeUnit::Nanoseconds,
> Some("UTC")). However, the code that constructs the Arrays seems to re-derive
> this column type as DataType::Timestamp(TimeUnit::Nanoseconds, None) (because
> the Parquet schema has no timezone information). And so, Parquet files that
> we were able to read successfully with our branch of Arrow circa October are
> now unreadable.
>
> I've attached an example of a Parquet file that demonstrates the problem.
> This file was created in Python (as most of our Parquet files are).
--
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