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<!DOCTYPE concept PUBLIC "-//OASIS//DTD DITA Concept//EN" "concept.dtd">
<concept rev="2.5.0 IMPALA-2499" id="optimize_partition_key_scans">

  <title>OPTIMIZE_PARTITION_KEY_SCANS Query Option (<keyword keyref="impala25"/> or higher only)</title>
  <titlealts audience="PDF"><navtitle>OPTIMIZE_PARTITION_KEY_SCANS</navtitle></titlealts>
  <prolog>
    <metadata>
      <data name="Category" value="Impala"/>
      <data name="Category" value="Impala Query Options"/>
      <data name="Category" value="Querying"/>
      <data name="Category" value="Performance"/>
      <data name="Category" value="Developers"/>
      <data name="Category" value="Data Analysts"/>
    </metadata>
  </prolog>

  <conbody>

    <p rev="2.5.0 IMPALA-2499">
      <indexterm audience="hidden">OPTIMIZE_PARTITION_KEY_SCANS query option</indexterm>
      Enables a fast code path for queries that apply simple aggregate functions to partition key
      columns: <codeph>MIN(<varname>key_column</varname>)</codeph>, <codeph>MAX(<varname>key_column</varname>)</codeph>,
      or <codeph>COUNT(DISTINCT <varname>key_column</varname>)</codeph>.
    </p>

    <p conref="../shared/impala_common.xml#common/type_boolean"/>
    <p conref="../shared/impala_common.xml#common/default_false_0"/>

    <note conref="../shared/impala_common.xml#common/one_but_not_true"/>

    <p conref="../shared/impala_common.xml#common/added_in_250"/>

    <p conref="../shared/impala_common.xml#common/usage_notes_blurb"/>

    <p>
      This optimization speeds up common <q>introspection</q> operations
      over partition key columns, for example determining the distinct values
      of partition keys.
    </p>

    <p>
      This optimization does not apply to <codeph>SELECT</codeph> statements
      that reference columns that are not partition keys. It also only applies
      when all the partition key columns in the <codeph>SELECT</codeph> statement
      are referenced in one of the following contexts:
      <ul>
        <li>
          <p>
            Within a <codeph>MAX()</codeph> or <codeph>MAX()</codeph>
            aggregate function or as the argument of any aggregate function with
            the <codeph>DISTINCT</codeph> keyword applied.
          </p>
        </li>
        <li>
          <p>
            Within a <codeph>WHERE</codeph>, <codeph>GROUP BY</codeph>
            or <codeph>HAVING</codeph> clause.
          </p>
        </li>
      </ul>
    </p>

    <p>
      This optimization is enabled by a query option because it skips some consistency checks
      and therefore can return slightly different partition values if partitions are in the
      process of being added, dropped, or loaded outside of Impala. Queries might exhibit different
      behavior depending on the setting of this option in the following cases:
    </p>

    <ul>
      <li>
        <p>
          If files are removed from a partition using HDFS or other non-Impala operations,
          there is a period until the next <codeph>REFRESH</codeph> of the table where regular
          queries fail at run time because they detect the missing files. With this optimization
          enabled, queries that evaluate only the partition key column values (not the contents of
          the partition itself) succeed, and treat the partition as if it still exists.
        </p>
      </li>
      <li>
        <p>
          If a partition contains any data files, but the data files do not contain any rows,
          a regular query considers that the partition does not exist. With this optimization
          enabled, the partition is treated as if it exists.
        </p>
        <p>
          If the partition includes no files at all, this optimization does not change the query
          behavior: the partition is considered to not exist whether or not this optimization is enabled.
        </p>
      </li>
    </ul>

    <p conref="../shared/impala_common.xml#common/example_blurb"/>

    <p>
      The following example shows initial schema setup and the default behavior of queries that
      return just the partition key column for a table:
    </p>

<codeblock>
-- Make a partitioned table with 3 partitions.
create table t1 (s string) partitioned by (year int);
insert into t1 partition (year=2015) values ('last year');
insert into t1 partition (year=2016) values ('this year');
insert into t1 partition (year=2017) values ('next year');

-- Regardless of the option setting, this query must read the
-- data files to know how many rows to return for each year value.
explain select year from t1;
+-----------------------------------------------------+
| Explain String                                      |
+-----------------------------------------------------+
| Estimated Per-Host Requirements: Memory=0B VCores=0 |
|                                                     |
| F00:PLAN FRAGMENT [UNPARTITIONED]                   |
|   00:SCAN HDFS [key_cols.t1]                        |
|      partitions=3/3 files=4 size=40B                |
|      table stats: 3 rows total                      |
|      column stats: all                              |
|      hosts=3 per-host-mem=unavailable               |
|      tuple-ids=0 row-size=4B cardinality=3          |
+-----------------------------------------------------+

-- The aggregation operation means the query does not need to read
-- the data within each partition: the result set contains exactly 1 row
-- per partition, derived from the partition key column value.
-- By default, Impala still includes a 'scan' operation in the query.
explain select distinct year from t1;
+------------------------------------------------------------------------------------+
| Explain String                                                                     |
+------------------------------------------------------------------------------------+
| Estimated Per-Host Requirements: Memory=0B VCores=0                                |
|                                                                                    |
| 01:AGGREGATE [FINALIZE]                                                            |
| |  group by: year                                                                  |
| |                                                                                  |
| 00:SCAN HDFS [key_cols.t1]                                                         |
|    partitions=0/0 files=0 size=0B                                                  |
+------------------------------------------------------------------------------------+
</codeblock>

    <p>
      The following examples show how the plan is made more efficient when the
      <codeph>OPTIMIZE_PARTITION_KEY_SCANS</codeph> option is enabled:
    </p>

<codeblock>
set optimize_partition_key_scans=1;
OPTIMIZE_PARTITION_KEY_SCANS set to 1

-- The aggregation operation is turned into a UNION internally,
-- with constant values known in advance based on the metadata
-- for the partitioned table.
explain select distinct year from t1;
+-----------------------------------------------------+
| Explain String                                      |
+-----------------------------------------------------+
| Estimated Per-Host Requirements: Memory=0B VCores=0 |
|                                                     |
| F00:PLAN FRAGMENT [UNPARTITIONED]                   |
|   01:AGGREGATE [FINALIZE]                           |
|   |  group by: year                                 |
|   |  hosts=1 per-host-mem=unavailable               |
|   |  tuple-ids=1 row-size=4B cardinality=3          |
|   |                                                 |
|   00:UNION                                          |
|      constant-operands=3                            |
|      hosts=1 per-host-mem=unavailable               |
|      tuple-ids=0 row-size=4B cardinality=3          |
+-----------------------------------------------------+

-- The same optimization applies to other aggregation queries
-- that only return values based on partition key columns:
-- MIN, MAX, COUNT(DISTINCT), and so on.
explain select min(year) from t1;
+-----------------------------------------------------+
| Explain String                                      |
+-----------------------------------------------------+
| Estimated Per-Host Requirements: Memory=0B VCores=0 |
|                                                     |
| F00:PLAN FRAGMENT [UNPARTITIONED]                   |
|   01:AGGREGATE [FINALIZE]                           |
|   |  output: min(year)                              |
|   |  hosts=1 per-host-mem=unavailable               |
|   |  tuple-ids=1 row-size=4B cardinality=1          |
|   |                                                 |
|   00:UNION                                          |
|      constant-operands=3                            |
|      hosts=1 per-host-mem=unavailable               |
|      tuple-ids=0 row-size=4B cardinality=3          |
+-----------------------------------------------------+
</codeblock>

  </conbody>
</concept>