Jianshi Huang created SPARK-5446:
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Summary: Parquet column pruning should work for Map and Struct
Key: SPARK-5446
URL: https://issues.apache.org/jira/browse/SPARK-5446
Project: Spark
Issue Type: Improvement
Components: SQL
Affects Versions: 1.2.0, 1.3.0
Reporter: Jianshi Huang
Consider the following query:
{code:sql}
select stddev_pop(variables.var1) stddev
from model
group by model_name
{code}
Where variables is a Struct containing many fields, similarly it can be a Map
with many key-value pairs.
During execution, SparkSQL will shuffle the whole map or struct column instead
of extracting the value first. The performance is very poor.
The optimized version could use a subquery:
{code:sql}
select stddev_pop(var) stddev
from (select variables.var1 as var, model_name from model) m
group by model_name
{code}
Where we extract the field/key-value only in the mapper side, so data being
shuffled is small.
Parquet already supports reading a single field/key-value in the storage level,
but SparkSQL currently doesn’t have optimization for it. This will be very
useful optimization for tables having Map or Struct with many columns.
Jianshi
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