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https://issues.apache.org/jira/browse/DRILL-5851?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16302683#comment-16302683
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ASF GitHub Bot commented on DRILL-5851:
---------------------------------------
Github user paul-rogers commented on a diff in the pull request:
https://github.com/apache/drill/pull/1059#discussion_r158593956
--- Diff:
exec/java-exec/src/main/java/org/apache/drill/exec/physical/impl/join/HashJoinBatch.java
---
@@ -305,11 +307,15 @@ public void executeBuildPhase() throws
SchemaChangeException, ClassTransformatio
//Setup the underlying hash table
// skip first batch if count is zero, as it may be an empty schema
batch
- if (right.getRecordCount() == 0) {
+ if (isFurtherProcessingRequired(rightUpstream) &&
right.getRecordCount() == 0) {
for (final VectorWrapper<?> w : right) {
w.clear();
}
rightUpstream = next(right);
+ if (isFurtherProcessingRequired(rightUpstream) &&
+ right.getRecordCount() > 0 && hashTable == null) {
+ setupHashTable();
--- End diff --
This handles an empty batch followed by a non-empty batch. Can we be sure
that there will only ever be a sequence of 0 or 1 empty batches? Might there be
a pathological scan that reads 20 (say) empty files, producing a series of 20
empty batches? In short, should the logic here be in a loop?
Did we create a test that checks for this case?
> Empty table during a join operation with a non empty table produces cast
> exception
> -----------------------------------------------------------------------------------
>
> Key: DRILL-5851
> URL: https://issues.apache.org/jira/browse/DRILL-5851
> Project: Apache Drill
> Issue Type: Bug
> Components: Execution - Relational Operators
> Affects Versions: 1.11.0
> Reporter: Hanumath Rao Maduri
> Assignee: Hanumath Rao Maduri
>
> Hash Join operation on tables with one table empty and the other non empty
> throws an exception
> {code}
> Error: SYSTEM ERROR: DrillRuntimeException: Join only supports implicit casts
> between 1. Numeric data
> 2. Varchar, Varbinary data 3. Date, Timestamp data Left type: VARCHAR, Right
> type: INT. Add explicit casts to avoid this error
> {code}
> Here is an example query with which it is reproducible.
> {code}
> select * from cp.`sample-data/nation.parquet` nation left outer join
> dfs.tmp.`2.csv` as two on two.a = nation.`N_COMMENT`;
> {code}
> the contents of 2.csv is empty (i.e not even header info).
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