MT_DOP Query Option
Sets the degree of intra-node parallelism used for certain operations that can benefit from multithreaded execution. You can specify values higher than zero to find the ideal balance of response time, memory usage, and CPU usage during statement processing.
The Impala execution engine is being revamped incrementally to add
additional parallelism within a single host for certain statements and
kinds of operations. The setting MT_DOP=0
uses the
"old" code path with limited intra-node parallelism.
Currently, the operations affected by the MT_DOP
query option are:
-
COMPUTE [INCREMENTAL] STATS
. Impala automatically setsMT_DOP=4
forCOMPUTE STATS
andCOMPUTE INCREMENTAL STATS
statements on Parquet tables. -
Queries with execution plans containing only scan and aggregation operators, or local joins that do not need data exchanges (such as for nested types). Other queries produce an error if
MT_DOP
is set to a non-zero value. Therefore, this query option is typically only set for the duration of specific long-running, CPU-intensive queries.
Type: integer
Default: 0
Because COMPUTE STATS
and COMPUTE INCREMENTAL STATS
statements for Parquet tables benefit substantially from extra intra-node
parallelism, Impala automatically sets MT_DOP=4
when computing stats
for Parquet tables.
Range: 0 to 64
Examples:
Any timing figures in the following examples are on a small, lightly loaded development cluster. Your mileage may vary. Speedups depend on many factors, including the number of rows, columns, and partitions within each table.
The following example shows how to run a COMPUTE STATS
statement against a Parquet table with or without an explicit MT_DOP
setting:
-- Explicitly setting MT_DOP to 0 selects the old code path.
set mt_dop = 0;
MT_DOP set to 0
-- The analysis for the billion rows is distributed among hosts,
-- but uses only a single core on each host.
compute stats billion_rows_parquet;
+-----------------------------------------+
| summary |
+-----------------------------------------+
| Updated 1 partition(s) and 2 column(s). |
+-----------------------------------------+
drop stats billion_rows_parquet;
-- Using 4 logical processors per host is faster.
set mt_dop = 4;
MT_DOP set to 4
compute stats billion_rows_parquet;
+-----------------------------------------+
| summary |
+-----------------------------------------+
| Updated 1 partition(s) and 2 column(s). |
+-----------------------------------------+
drop stats billion_rows_parquet;
-- Unsetting the option reverts back to its default.
-- Which for COMPUTE STATS and a Parquet table is 4,
-- so again it uses the fast path.
unset MT_DOP;
Unsetting option MT_DOP
compute stats billion_rows_parquet;
+-----------------------------------------+
| summary |
+-----------------------------------------+
| Updated 1 partition(s) and 2 column(s). |
+-----------------------------------------+
The following example shows the effects of setting MT_DOP
for a query involving only scan and aggregation operations for a Parquet table:
set mt_dop = 0;
MT_DOP set to 0
-- COUNT(DISTINCT) for a unique column is CPU-intensive.
select count(distinct id) from billion_rows_parquet;
+--------------------+
| count(distinct id) |
+--------------------+
| 1000000000 |
+--------------------+
Fetched 1 row(s) in 67.20s
set mt_dop = 16;
MT_DOP set to 16
-- Introducing more intra-node parallelism for the aggregation
-- speeds things up, and potentially reduces memory overhead by
-- reducing the number of scanner threads.
select count(distinct id) from billion_rows_parquet;
+--------------------+
| count(distinct id) |
+--------------------+
| 1000000000 |
+--------------------+
Fetched 1 row(s) in 17.19s
The following example shows how queries that are not compatible with non-zero
MT_DOP
settings produce an error when MT_DOP
is set:
set mt_dop=1;
MT_DOP set to 1
select * from a1 inner join a2
on a1.id = a2.id limit 4;
ERROR: NotImplementedException: MT_DOP not supported for plans with
base table joins or table sinks.
Related information: