ORDER BY Clause

The familiar ORDER BY clause of a SELECT statement sorts the result set based on the values from one or more columns.

For distributed queries, this is a relatively expensive operation, because the entire result set must be produced and transferred to one node before the sorting can happen. This 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.

Note:

In Impala 1.4.0 and higher, the LIMIT clause is now optional (rather than required) for queries that use the ORDER BY clause. Impala automatically uses a temporary disk work area to perform the sort if the sort operation would otherwise exceed the Impala memory limit for a particular DataNode.

Syntax:

The full syntax for the ORDER BY clause is:

  1. ORDER BY col_ref [, col_ref ...] [ASC | DESC] [NULLS FIRST | NULLS LAST]
  3. 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]($ac1745119389e484.md#order_by) clause to also use a [LIMIT]($4b8e0b571b08df96.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 node, 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:

  1. CREATE TABLE games (id BIGINT, score ARRAY <BIGINT>) STORED AS PARQUET;
  2. ...use LOAD DATA to load externally created Parquet files into the table...
  3. SELECT id FROM games ORDER BY score DESC;
  4. 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 pseudocolumn that represents each array element.

  1. SELECT id, item FROM games, games.score
  2.   WHERE item > 1000000
  3. 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.

  1. CREATE TABLE games2 (id BIGINT, play array < struct <game_name: string, score: BIGINT, high_score: boolean> >) STORED AS PARQUET
  2. ...use LOAD DATA to load externally created Parquet files into the table...
  3. SELECT id, item.game_name, item.score FROM games2, games2.play
  4.   WHERE item.score > 1000000
  5. ORDER BY id, item.score DESC;
  7. CREATE TABLE games3 (id BIGINT, play ARRAY < MAP <STRING, BIGINT> >) STORED AS PARQUET;
  8. ...use LOAD DATA to load externally created Parquet files into the table...
  9. SELECT id, info.key AS k, info.value AS v from games3, games3.play AS plays, games3.play.item AS info
  10.   WHERE info.KEY = 'score' AND info.VALUE > 1000000
  11. 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 data node 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:

  1. SELECT user_id AS "Top 10 Visitors", SUM(page_views) FROM web_stats
  2.   GROUP BY page_views, user_id
  3.   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:

  1. SELECT page_title AS "Page 1 of search results", page_url FROM search_content
  2.   WHERE LOWER(page_title) LIKE '%game%')
  3.   ORDER BY page_title LIMIT 10 OFFSET 0;
  4. SELECT page_title AS "Page 2 of search results", page_url FROM search_content
  5.   WHERE LOWER(page_title) LIKE '%game%')
  6.   ORDER BY page_title LIMIT 10 OFFSET 10;
  7. SELECT page_title AS "Page 3 of search results", page_url FROM search_content
  8.   WHERE LOWER(page_title) LIKE '%game%')
  9.   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 DataNodes, each node 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 DataNode 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 DataNode, 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 DataNode (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 . These files are removed when the operation finishes. (Multiple concurrent queries can perform operations that use the “spill to disk” technique, without any name conflicts for these temporary files.) You can specify a different location by starting the impalad daemon with the --scratch_dirs="path_to_directory" configuration option. You can specify a single directory, or a comma-separated list of directories. The scratch directories must be on the local filesystem, not in HDFS. You might specify different directory paths for different hosts, depending on the capacity and speed of the available storage devices. In Impala 2.3 or higher, Impala successfully starts (with a warning Impala successfully starts (with a warning written to the log) if it cannot create or read and write files in one of the scratch directories. If there is less than 1 GB free on the filesystem where that directory resides, Impala still runs, but writes a warning message to its log. If Impala encounters an error reading or writing files in a scratch directory during a query, Impala logs the error and the query fails.

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 on different data nodes, 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:

  1. [localhost:21000] > create table unsorted (x bigint);
  2. [localhost:21000] > insert into unsorted values (1), (9), (3), (7), (5), (8), (4), (6), (2);
  3. [localhost:21000] > create view sorted_view as select x from unsorted order by x;
  4. [localhost:21000] > select x from sorted_view; -- ORDER BY clause in view has no effect.
  5. +---+
  6. | x |
  7. +---+
  8. | 1 |
  9. | 9 |
  10. | 3 |
  11. | 7 |
  12. | 5 |
  13. | 8 |
  14. | 4 |
  15. | 6 |
  16. | 2 |
  17. +---+
  18. [localhost:21000] > select x from sorted_view order by x; -- View query requires ORDER BY at outermost level.
  19. +---+
  20. | x |
  21. +---+
  22. | 1 |
  23. | 2 |
  24. | 3 |
  25. | 4 |
  26. | 5 |
  27. | 6 |
  28. | 7 |
  29. | 8 |
  30. | 9 |
  31. +---+
  32. [localhost:21000] > create view top_3_view as select x from unsorted order by x limit 3;
  33. [localhost:21000] > select x from top_3_view; -- ORDER BY and LIMIT together in view definition are preserved.
  34. +---+
  35. | x |
  36. +---+
  37. | 1 |
  38. | 2 |
  39. | 3 |
  40. +---+

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 DataNode, 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.

  1. [localhost:21000] > create table numbers (x int);
  2. [localhost:21000] > insert into numbers values (1), (null), (2), (null), (3);
  3. [localhost:21000] > select x from numbers order by x nulls first;
  4. +------+
  5. | x    |
  6. +------+
  7. | NULL |
  8. | NULL |
  9. | 1    |
  10. | 2    |
  11. | 3    |
  12. +------+
  13. [localhost:21000] > select x from numbers order by x desc nulls first;
  14. +------+
  15. | x    |
  16. +------+
  17. | NULL |
  18. | NULL |
  19. | 3    |
  20. | 2    |
  21. | 1    |
  22. +------+
  23. [localhost:21000] > select x from numbers order by x nulls last;
  24. +------+
  25. | x    |
  26. +------+
  27. | 1    |
  28. | 2    |
  29. | 3    |
  30. | NULL |
  31. | NULL |
  32. +------+
  33. [localhost:21000] > select x from numbers order by x desc nulls last;
  34. +------+
  35. | x    |
  36. +------+
  37. | 3    |
  38. | 2    |
  39. | 1    |
  40. | NULL |
  41. | NULL |
  42. +------+

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