siddharthteotia commented on a change in pull request #4877: Results in
ResultTable if responseFormat=sql
URL: https://github.com/apache/incubator-pinot/pull/4877#discussion_r353420479
##########
File path:
pinot-core/src/main/java/org/apache/pinot/core/query/reduce/DistinctDataTableReducer.java
##########
@@ -115,18 +140,31 @@ public void reduceAndSetResults(String tableName,
DataSchema dataSchema, Map<Ser
}
resultSet.add(distinctRow);
}
+ return new SelectionResults(Arrays.asList(columnNames), resultSet);
+ }
- // Up until now, we have treated DISTINCT similar to another aggregation
function even in terms
- // of the result from function and merging results.
- // However, the DISTINCT query is just another SELECTION style query from
the user's point
- // of view and will return one or records in the result table for the
column(s) selected and so
- // for that reason, response from broker should be a selection query
result.
- brokerResponseNative.setSelectionResults((new
SelectionResults(Arrays.asList(columnNames), resultSet)));
+ private ResultTable reduceToResultTable(DistinctTable distinctTable) {
+ List<Object[]> resultSet = new ArrayList<>(distinctTable.size());
+ Iterator<Record> iterator = distinctTable.iterator();
+ while (iterator.hasNext()) {
+ Record record = iterator.next();
+ resultSet.add(record.getValues());
+ }
+ DataSchema finalDataSchema = getResultTableDataSchema();
+ return new ResultTable(finalDataSchema, resultSet);
}
private String[] getDistinctColumns() {
return _brokerRequest.getAggregationsInfo().get(0).getAggregationParams()
.get(FunctionCallAstNode.COLUMN_KEY_IN_AGGREGATION_INFO)
.split(FunctionCallAstNode.DISTINCT_MULTI_COLUMN_SEPARATOR);
}
+
+ private DataSchema getResultTableDataSchema() {
+ String[] columns = getDistinctColumns();
+ DataSchema.ColumnDataType[] columnDataTypes = new
DataSchema.ColumnDataType[columns.length];
+ // TODO: there's no way currently to get the data types of the distinct
columns
Review comment:
You can do distinctTable.getDataSchema() and that should have both column
names and types.
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