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https://issues.apache.org/jira/browse/DRILL-7578?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17038836#comment-17038836
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ASF GitHub Bot commented on DRILL-7578:
---------------------------------------
paul-rogers commented on pull request #1978: DRILL-7578: HDF5 Metadata Queries
Fail with Large Files
URL: https://github.com/apache/drill/pull/1978#discussion_r380487624
##########
File path:
contrib/format-hdf5/src/main/java/org/apache/drill/exec/store/hdf5/HDF5BatchReader.java
##########
@@ -92,6 +93,20 @@
private static final String LONG_COLUMN_NAME = "long_data";
+ private static final String DATA_SIZE_COLUMN_NAME = "data_size";
+
+ private static final String ELEMENT_COUNT_NAME = "element_count";
+
+ private static final String IS_TIMESTAMP_NAME = "is_timestamp";
Review comment:
The two `is` columns appear mutually exclusive. I wonder, does it make sense
to define an `extended_type` column if `data_type` is the Drill type? That is,
for most columns, `extended_type` would be null. For these two it would be, say
`TIMESTAMP` or `TIME_DURATION`. Though, truth be told, Drill has `TIMESTAMP`
and `INTERVAL` columns, so if we mapped the HDF5 type to these Drill types, we
would not need the extended type (or these two Boolean columns).
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> HDF5 Metadata Queries Fail with Large Files
> -------------------------------------------
>
> Key: DRILL-7578
> URL: https://issues.apache.org/jira/browse/DRILL-7578
> Project: Apache Drill
> Issue Type: Bug
> Affects Versions: 1.18.0
> Reporter: Charles Givre
> Assignee: Charles Givre
> Priority: Major
> Fix For: 1.18.0
>
>
> With large files, Drill runs out of memory when attempting to project large
> datasets in the metadata.
> This PR adds a configuration option which removes the dataset projection from
> metadata queries and fixes this issue.
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