Bruce Robbins created SPARK-25164:
-------------------------------------
Summary: Parquet reader builds entire list of columns once for
each column
Key: SPARK-25164
URL: https://issues.apache.org/jira/browse/SPARK-25164
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.4.0
Reporter: Bruce Robbins
{{VectorizedParquetRecordReader.initializeInternal}} loops through each column,
and for each column it calls
{noformat}
requestedSchema.getColumns().get(i)
{noformat}
However, {{MessageType.getColumns}} will build the entire column list from
getPaths(0).
{noformat}
public List<ColumnDescriptor> getColumns() {
List<String[]> paths = this.getPaths(0);
List<ColumnDescriptor> columns = new
ArrayList<ColumnDescriptor>(paths.size());
for (String[] path : paths) {
// TODO: optimize this
PrimitiveType primitiveType = getType(path).asPrimitiveType();
columns.add(new ColumnDescriptor(
path,
primitiveType,
getMaxRepetitionLevel(path),
getMaxDefinitionLevel(path)));
}
return columns;
}
{noformat}
This means that for each parquet file, this routine indirectly iterates
colCount*colCount times.
This is actually not particularly noticeable unless you have:
- many parquet files
- many columns
To verify that this is an issue, I created a 1 million record parquet table
with 6000 columns of type double and 67 files (so initializeInternal is called
67 times). I ran the following query:
{noformat}
sql("select * from 6000_1m_double where id1 = 1").collect
{noformat}
I used Spark from the master branch. I had 8 executor threads. The filter
returns only a few thousand records. The query ran (on average) for 6.4 minutes.
Then I cached the column list at the top of {{initializeInternal}} as follows:
{noformat}
List<ColumnDescriptor> columnCache = requestedSchema.getColumns();
{noformat}
Then I changed {{initializeInternal}} to use {{columnCache}} rather than
{{requestedSchema.getColumns()}}.
With the column cache variable, the same query runs in 5 minutes. So with my
simple query, you save %22 of time by not rebuilding the column list for each
column.
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