ORDER BY Clause
The ORDER BY
clause of a SELECT
statement sorts the result set based on the values from one or more columns.
First, data is sorted locally by each impalad
daemon, then streamed to the coordinator daemon, which merges the sorted result sets. For distributed queries, this is a relatively expensive operation and can require more memory capacity than a query without ORDER BY
. Even if the query takes approximately the same time to finish with or without the ORDER BY
clause, subjectively it can appear slower because no results are available until all processing is finished, rather than results coming back gradually as rows matching the WHERE
clause are found. Therefore, if you only need the first N results from the sorted result set, also include the LIMIT
clause, which reduces network overhead and the memory requirement on the coordinator node.
Syntax:
The full syntax for the ORDER BY
clause is:
ORDER BY col_ref [, col_ref ...] [ASC | DESC] [NULLS FIRST | NULLS LAST]
col_ref ::= column_name | integer_literal
Although the most common usage is ORDER BY column_name
, you can also specify ORDER BY 1
to sort by the first column of the result set, ORDER BY 2
to sort by the second column, and so on. The number must be a numeric literal, not some other kind of constant expression. (If the argument is some other expression, even a STRING
value, the query succeeds but the order of results is undefined.)
ORDER BY column_number
can only be used when the query explicitly lists the columns in the SELECT
list, not with SELECT *
queries.
Ascending and descending sorts:
The default sort order (the same as using the ASC
keyword) puts the smallest values at the start of the result set, and the largest values at the end. Specifying the DESC
keyword reverses that order.
Sort order for NULL values:
See NULL for details about how NULL
values are positioned in the sorted result set, and how to use the NULLS FIRST
and NULLS LAST
clauses. (The sort position for NULL
values in ORDER BY ... DESC
queries is changed in Impala 1.2.1 and higher to be more standards-compliant, and the NULLS FIRST
and NULLS LAST
keywords are new in Impala 1.2.1.)
Prior to Impala 1.4.0, Impala required any query including an [ORDER BY]($41f0e5f6601e9e60.md#order_by)
clause to also use a [LIMIT]($bcd629c2564e18b4.md#limit)
clause. In Impala 1.4.0 and higher, the LIMIT
clause is optional for ORDER BY
queries. In cases where sorting a huge result set requires enough memory to exceed the Impala memory limit for a particular executor Impala daemon, Impala automatically uses a temporary disk work area to perform the sort operation.
Complex type considerations:
In Impala 2.3 and higher, the complex data types STRUCT
, ARRAY
, and MAP
are available. These columns cannot be referenced directly in the ORDER BY
clause. When you query a complex type column, you use join notation to “unpack” the elements of the complex type, and within the join query you can include an ORDER BY
clause to control the order in the result set of the scalar elements from the complex type. See Complex Types (Impala 2.3 or higher only) for details about Impala support for complex types.
The following query shows how a complex type column cannot be directly used in an ORDER BY
clause:
CREATE TABLE games (id BIGINT, score ARRAY <BIGINT>) STORED AS PARQUET;
...use LOAD DATA to load externally created Parquet files into the table...
SELECT id FROM games ORDER BY score DESC;
ERROR: AnalysisException: ORDER BY expression 'score' with complex type 'ARRAY<BIGINT>' is not supported.
Examples:
The following query retrieves the user ID and score, only for scores greater than one million, with the highest scores for each user listed first. Because the individual array elements are now represented as separate rows in the result set, they can be used in the ORDER BY
clause, referenced using the ITEM
pseudo-column that represents each array element.
SELECT id, item FROM games, games.score
WHERE item > 1000000
ORDER BY id, item desc;
The following queries use similar ORDER BY
techniques with variations of the GAMES
table, where the complex type is an ARRAY
containing STRUCT
or MAP
elements to represent additional details about each game that was played. For an array of structures, the fields of the structure are referenced as ITEM.field_name
. For an array of maps, the keys and values within each array element are referenced as ITEM.KEY
and ITEM.VALUE
.
CREATE TABLE games2 (id BIGINT, play array < struct <game_name: string, score: BIGINT, high_score: boolean> >) STORED AS PARQUET
...use LOAD DATA to load externally created Parquet files into the table...
SELECT id, item.game_name, item.score FROM games2, games2.play
WHERE item.score > 1000000
ORDER BY id, item.score DESC;
CREATE TABLE games3 (id BIGINT, play ARRAY < MAP <STRING, BIGINT> >) STORED AS PARQUET;
...use LOAD DATA to load externally created Parquet files into the table...
SELECT id, info.key AS k, info.value AS v from games3, games3.play AS plays, games3.play.item AS info
WHERE info.KEY = 'score' AND info.VALUE > 1000000
ORDER BY id, info.value desc;
Usage notes:
Although the LIMIT
clause is now optional on ORDER BY
queries, if your query only needs some number of rows that you can predict in advance, use the LIMIT
clause to reduce unnecessary processing. For example, if the query has a clause LIMIT 10
, each executor Impala daemon sorts its portion of the relevant result set and only returns 10 rows to the coordinator node. The coordinator node picks the 10 highest or lowest row values out of this small intermediate result set.
If an ORDER BY
clause is applied to an early phase of query processing, such as a subquery or a view definition, Impala ignores the ORDER BY
clause. To get ordered results from a subquery or view, apply an ORDER BY
clause to the outermost or final SELECT
level.
ORDER BY
is often used in combination with LIMIT
to perform “top-N” queries:
SELECT user_id AS "Top 10 Visitors", SUM(page_views) FROM web_stats
GROUP BY page_views, user_id
ORDER BY SUM(page_views) DESC LIMIT 10;
ORDER BY
is sometimes used in combination with OFFSET
and LIMIT
to paginate query results, although it is relatively inefficient to issue multiple queries like this against the large tables typically used with Impala:
SELECT page_title AS "Page 1 of search results", page_url FROM search_content
WHERE LOWER(page_title) LIKE '%game%')
ORDER BY page_title LIMIT 10 OFFSET 0;
SELECT page_title AS "Page 2 of search results", page_url FROM search_content
WHERE LOWER(page_title) LIKE '%game%')
ORDER BY page_title LIMIT 10 OFFSET 10;
SELECT page_title AS "Page 3 of search results", page_url FROM search_content
WHERE LOWER(page_title) LIKE '%game%')
ORDER BY page_title LIMIT 10 OFFSET 20;
Internal details:
Impala sorts the intermediate results of an ORDER BY
clause in memory whenever practical. In a cluster of N executor Impala daemons, each daemon sorts roughly 1/Nth of the result set, the exact proportion varying depending on how the data matching the query is distributed in HDFS.
If the size of the sorted intermediate result set on any executor Impala daemon would cause the query to exceed the Impala memory limit, Impala sorts as much as practical in memory, then writes partially sorted data to disk. (This technique is known in industry terminology as “external sorting” and “spilling to disk”.) As each 8 MB batch of data is written to disk, Impala frees the corresponding memory to sort a new 8 MB batch of data. When all the data has been processed, a final merge sort operation is performed to correctly order the in-memory and on-disk results as the result set is transmitted back to the coordinator node. When external sorting becomes necessary, Impala requires approximately 60 MB of RAM at a minimum for the buffers needed to read, write, and sort the intermediate results. If more RAM is available on the Impala daemon, Impala will use the additional RAM to minimize the amount of disk I/O for sorting.
This external sort technique is used as appropriate on each Impala daemon (possibly including the coordinator node) to sort the portion of the result set that is processed on that node. When the sorted intermediate results are sent back to the coordinator node to produce the final result set, the coordinator node uses a merge sort technique to produce a final sorted result set without using any extra resources on the coordinator node.
Configuration for disk usage:
By default, intermediate files used during large sort, join, aggregation, or analytic function operations are stored in the directory /tmp/impala-scratch, and these intermediate files are removed when the operation finishes. You can specify a different location by starting the impalad daemon with the ‑‑scratch_dirs="path_to_directory"
configuration option.
Sorting considerations: Although you can specify an ORDER BY
clause in an INSERT ... SELECT
statement, any ORDER BY
clause is ignored and the results are not necessarily sorted. An INSERT ... SELECT
operation potentially creates many different data files, prepared by different executor Impala daemons, and therefore the notion of the data being stored in sorted order is impractical.
An ORDER BY
clause without an additional LIMIT
clause is ignored in any view definition. If you need to sort the entire result set from a view, use an ORDER BY
clause in the SELECT
statement that queries the view. You can still make a simple “top 10” report by combining the ORDER BY
and LIMIT
clauses in the same view definition:
[localhost:21000] > create table unsorted (x bigint);
[localhost:21000] > insert into unsorted values (1), (9), (3), (7), (5), (8), (4), (6), (2);
[localhost:21000] > create view sorted_view as select x from unsorted order by x;
[localhost:21000] > select x from sorted_view; -- ORDER BY clause in view has no effect.
+---+
| x |
+---+
| 1 |
| 9 |
| 3 |
| 7 |
| 5 |
| 8 |
| 4 |
| 6 |
| 2 |
+---+
[localhost:21000] > select x from sorted_view order by x; -- View query requires ORDER BY at outermost level.
+---+
| x |
+---+
| 1 |
| 2 |
| 3 |
| 4 |
| 5 |
| 6 |
| 7 |
| 8 |
| 9 |
+---+
[localhost:21000] > create view top_3_view as select x from unsorted order by x limit 3;
[localhost:21000] > select x from top_3_view; -- ORDER BY and LIMIT together in view definition are preserved.
+---+
| x |
+---+
| 1 |
| 2 |
| 3 |
+---+
With the lifting of the requirement to include a LIMIT
clause in every ORDER BY
query (in Impala 1.4 and higher):
- Now the use of scratch disk space raises the possibility of an “out of disk space” error on a particular Impala daemon, as opposed to the previous possibility of an “out of memory” error. Make sure to keep at least 1 GB free on the filesystem used for temporary sorting work.
In Impala 1.2.1 and higher, all NULL
values come at the end of the result set for ORDER BY ... ASC
queries, and at the beginning of the result set for ORDER BY ... DESC
queries. In effect, NULL
is considered greater than all other values for sorting purposes. The original Impala behavior always put NULL
values at the end, even for ORDER BY ... DESC
queries. The new behavior in Impala 1.2.1 makes Impala more compatible with other popular database systems. In Impala 1.2.1 and higher, you can override or specify the sorting behavior for NULL
by adding the clause NULLS FIRST
or NULLS LAST
at the end of the ORDER BY
clause.
[localhost:21000] > create table numbers (x int);
[localhost:21000] > insert into numbers values (1), (null), (2), (null), (3);
[localhost:21000] > select x from numbers order by x nulls first;
+------+
| x |
+------+
| NULL |
| NULL |
| 1 |
| 2 |
| 3 |
+------+
[localhost:21000] > select x from numbers order by x desc nulls first;
+------+
| x |
+------+
| NULL |
| NULL |
| 3 |
| 2 |
| 1 |
+------+
[localhost:21000] > select x from numbers order by x nulls last;
+------+
| x |
+------+
| 1 |
| 2 |
| 3 |
| NULL |
| NULL |
+------+
[localhost:21000] > select x from numbers order by x desc nulls last;
+------+
| x |
+------+
| 3 |
| 2 |
| 1 |
| NULL |
| NULL |
+------+
Related information:
See SELECT Statement for further examples of queries with the ORDER BY
clause.
Analytic functions use the ORDER BY
clause in a different context to define the sequence in which rows are analyzed. See Impala Analytic Functions for details.
Parent topic: SELECT Statement