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https://issues.apache.org/jira/browse/DRILL-7578?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17039528#comment-17039528
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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_r380982462
##########
File path:
contrib/format-hdf5/src/test/java/org/apache/drill/exec/store/hdf5/TestHDF5Format.java
##########
@@ -98,9 +98,9 @@ public void testStarQuery() throws Exception {
testBuilder()
.sqlQuery("SELECT * FROM dfs.`hdf5/dset.h5`")
- .unOrdered()
- .baselineColumns("path", "data_type", "file_name", "int_data")
- .baselineValues("/dset", "DATASET", "dset.h5", finalList)
+ .ordered()
Review comment:
Agreed. The point is not so much to change what you have here. Rather, it is
to learn what more Drill should provide. Some other random examples of nested
schemas are 1) REST calls, 2) Zip archives, 3) Iceberg files, 4) the JDBC
storage plugin.
I'm sure these are all done either not at all (Zip, Iceberg) or via ad-hoc
code (JDBC). The lesson is that Drill probably needs a way to support nested
schemas; not all data sources are Parquet or JSON files on HDFS.
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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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