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https://issues.apache.org/jira/browse/DRILL-5797?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16537213#comment-16537213
]
ASF GitHub Bot commented on DRILL-5797:
---------------------------------------
arina-ielchiieva closed pull request #976: DRILL-5797: Choose parquet reader
from read columns
URL: https://github.com/apache/drill/pull/976
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git
a/exec/java-exec/src/main/java/org/apache/drill/exec/store/parquet/ParquetScanBatchCreator.java
b/exec/java-exec/src/main/java/org/apache/drill/exec/store/parquet/ParquetScanBatchCreator.java
index 60179482fc3..82764285e99 100644
---
a/exec/java-exec/src/main/java/org/apache/drill/exec/store/parquet/ParquetScanBatchCreator.java
+++
b/exec/java-exec/src/main/java/org/apache/drill/exec/store/parquet/ParquetScanBatchCreator.java
@@ -26,6 +26,8 @@
import com.google.common.base.Stopwatch;
import com.google.common.collect.Maps;
import org.apache.drill.common.exceptions.ExecutionSetupException;
+import org.apache.drill.common.expression.PathSegment;
+import org.apache.drill.common.expression.SchemaPath;
import org.apache.drill.exec.ExecConstants;
import org.apache.drill.exec.ops.FragmentContext;
import org.apache.drill.exec.ops.OperatorContext;
@@ -37,12 +39,15 @@
import org.apache.drill.exec.store.dfs.DrillFileSystem;
import org.apache.drill.exec.store.parquet.columnreaders.ParquetRecordReader;
import org.apache.drill.exec.store.parquet2.DrillParquetReader;
+import org.apache.drill.exec.util.Utilities;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.parquet.column.ColumnDescriptor;
import org.apache.parquet.hadoop.CodecFactory;
import org.apache.parquet.hadoop.ParquetFileReader;
import org.apache.parquet.hadoop.metadata.ParquetMetadata;
+import org.apache.parquet.io.InvalidRecordException;
+import org.apache.parquet.schema.GroupType;
import org.apache.parquet.schema.MessageType;
import org.apache.parquet.schema.Type;
@@ -119,7 +124,7 @@ public ScanBatch getBatch(FragmentContext context,
ParquetRowGroupScan rowGroupS
if (logger.isDebugEnabled()) {
logger.debug(containsCorruptDates.toString());
}
- if
(!context.getOptions().getOption(ExecConstants.PARQUET_NEW_RECORD_READER).bool_val
&& !isComplex(footers.get(e.getPath()))) {
+ if
(!context.getOptions().getOption(ExecConstants.PARQUET_NEW_RECORD_READER).bool_val
&& !isComplex(footers.get(e.getPath()), rowGroupScan.getColumns())) {
readers.add(
new ParquetRecordReader(
context, e.getPath(), e.getRowGroupIndex(),
e.getNumRecordsToRead(), fs,
@@ -156,20 +161,49 @@ public ScanBatch getBatch(FragmentContext context,
ParquetRowGroupScan rowGroupS
return new ScanBatch(rowGroupScan, context, oContext, readers,
implicitColumns);
}
- private static boolean isComplex(ParquetMetadata footer) {
+ private static boolean isComplex(ParquetMetadata footer, List<SchemaPath>
columns) {
+ /**
+ * ParquetRecordReader is not able to read any nested columns and is not
able to handle repeated columns.
+ * It only handles flat column and optional column.
+ * If it is a wildcard query, we check every columns in the metadata.
+ * If not, we only check the projected columns.
+ * We only check the first level columns because :
+ * - if we need a.b, it means a is a complex type, no need to check b as
we don't handle complex type.
+ * - if we need a[10], a is repeated, ie its repetiton level is greater
than 0
+ * - if we need a, it is at the first level of the schema.
+ */
MessageType schema = footer.getFileMetaData().getSchema();
-
- for (Type type : schema.getFields()) {
- if (!type.isPrimitive()) {
- return true;
+ if (Utilities.isStarQuery(columns)) {
+ for (Type type : schema.getFields()) {
+ if (!type.isPrimitive()) {
+ return true;
+ }
}
- }
- for (ColumnDescriptor col : schema.getColumns()) {
- if (col.getMaxRepetitionLevel() > 0) {
- return true;
+ for (ColumnDescriptor col : schema.getColumns()) {
+ if (col.getMaxRepetitionLevel() > 0) {
+ return true;
+ }
+ }
+ return false;
+ } else {
+ for (SchemaPath column : columns) {
+ if (isColumnComplex(schema, column)) {
+ return true;
+ }
}
+ return false;
+ }
+ }
+
+ private static boolean isColumnComplex(GroupType grouptype, SchemaPath
column) {
+ try {
+ Type type =
grouptype.getType(column.getRootSegment().getPath().toLowerCase());
+ return type.isRepetition(Type.Repetition.REPEATED) ||
!type.isPrimitive();
+ }
+ catch(InvalidRecordException e) {
+ //if the type does exist, we will fill with null so it is a simple type.
+ return false;
}
- return false;
}
}
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> Use more often the new parquet reader
> -------------------------------------
>
> Key: DRILL-5797
> URL: https://issues.apache.org/jira/browse/DRILL-5797
> Project: Apache Drill
> Issue Type: Improvement
> Components: Storage - Parquet
> Reporter: Damien Profeta
> Assignee: Oleksandr Kalinin
> Priority: Major
> Fix For: 1.15.0
>
>
> The choice of using the regular parquet reader of the optimized one is based
> of what type of columns is in the file. But the columns that are read by the
> query doesn't matter. We can increase a little bit the cases where the
> optimized reader is used by checking is the projected column are simple or
> not.
> This is an optimization waiting for the fast parquet reader to handle complex
> structure.
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