This describes the syntax of SELECT clauses ORDER BY, SORT BY, CLUSTER BY, and DISTRIBUTE BY. See Select Syntax for general information.
The ORDER BY syntax in Hive QL is similar to the syntax of ORDER BY in SQL language.
colOrder: ( ASC | DESC ) colNullOrder: (NULLS FIRST | NULLS LAST) -- (Note: Available in Hive 2.1.0 and later) orderBy: ORDER BY colName colOrder? colNullOrder? (',' colName colOrder? colNullOrder?)* query: SELECT expression (',' expression)* FROM src orderBy
There are some limitations in the "order by" clause. In the strict mode (i.e., hive.mapred.mode=strict), the order by clause has to be followed by a "limit" clause. The limit clause is not necessary if you set hive.mapred.mode to nonstrict. The reason is that in order to impose total order of all results, there has to be one reducer to sort the final output. If the number of rows in the output is too large, the single reducer could take a very long time to finish.
Note that columns are specified by name, not by position number. However in Hive 0.11.0 and later, columns can be specified by position when configured as follows:
For Hive 0.11.0 through 2.1.x, set hive.groupby.orderby.position.alias to true (the default is false).
For Hive 2.2.0 and later, hive.orderby.position.alias is true by default.
The default sorting order is ascending (ASC).
In Hive 2.1.0 and later, specifying the null sorting order for each of the columns in the "order by" clause is supported. The default null sorting order for ASC order is NULLS FIRST, while the default null sorting order for DESC order is NULLS LAST.
The SORT BY syntax is similar to the syntax of ORDER BY in SQL language.
colOrder: ( ASC | DESC ) sortBy: SORT BY colName colOrder? (',' colName colOrder?)* query: SELECT expression (',' expression)* FROM src sortBy
Hive uses the columns in SORT BY to sort the rows before feeding the rows to a reducer. The sort order will be dependent on the column types. If the column is of numeric type, then the sort order is also in numeric order. If the column is of string type, then the sort order will be lexicographical order.
Hive supports SORT BY which sorts the data per reducer. The difference between "order by" and "sort by" is that the former guarantees total order in the output while the latter only guarantees ordering of the rows within a reducer. If there are more than one reducer, "sort by" may give partially ordered final results.
Note: It may be confusing as to the difference between SORT BY alone of a single column and CLUSTER BY. The difference is that CLUSTER BY partitions by the field and SORT BY if there are multiple reducers partitions randomly in order to distribute data (and load) uniformly across the reducers.
Basically, the data in each reducer will be sorted according to the order that the user specified. The following example shows
SELECT key, value FROM src SORT BY key ASC, value DESC
The query had 2 reducers, and the output of each is:
0 5 0 3 3 6 9 1
0 4 0 3 1 1 2 5
After a transform, variable types are generally considered to be strings, meaning that numeric data will be sorted lexicographically. To overcome this, a second SELECT statement with casts can be used before using SORT BY.
FROM (FROM (FROM src SELECT TRANSFORM(value) USING 'mapper' AS value, count) mapped SELECT cast(value as double) AS value, cast(count as int) AS count SORT BY value, count) sorted SELECT TRANSFORM(value, count) USING 'reducer' AS whatever
Cluster By and Distribute By are used mainly with the Transform/Map-Reduce Scripts. But, it is sometimes useful in SELECT statements if there is a need to partition and sort the output of a query for subsequent queries.
Cluster By is a short-cut for both Distribute By and Sort By.
Hive uses the columns in Distribute By to distribute the rows among reducers. All rows with the same Distribute By columns will go to the same reducer. However, Distribute By does not guarantee clustering or sorting properties on the distributed keys.
For example, we are Distributing By x on the following 5 rows to 2 reducer:
x1 x2 x4 x3 x1
Reducer 1 got
x1 x2 x1
Reducer 2 got
Note that all rows with the same key x1 is guaranteed to be distributed to the same reducer (reducer 1 in this case), but they are not guaranteed to be clustered in adjacent positions.
In contrast, if we use Cluster By x, the two reducers will further sort rows on x:
Reducer 1 got
x1 x1 x2
Reducer 2 got
Instead of specifying Cluster By, the user can specify Distribute By and Sort By, so the partition columns and sort columns can be different. The usual case is that the partition columns are a prefix of sort columns, but that is not required.
SELECT col1, col2 FROM t1 CLUSTER BY col1
SELECT col1, col2 FROM t1 DISTRIBUTE BY col1 SELECT col1, col2 FROM t1 DISTRIBUTE BY col1 SORT BY col1 ASC, col2 DESC
FROM ( FROM pv_users MAP ( pv_users.userid, pv_users.date ) USING 'map_script' AS c1, c2, c3 DISTRIBUTE BY c2 SORT BY c2, c1) map_output INSERT OVERWRITE TABLE pv_users_reduced REDUCE ( map_output.c1, map_output.c2, map_output.c3 ) USING 'reduce_script' AS date, count;