Lateral View Syntax
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Description
Lateral view is used in conjunction with user-defined table generating functions such as explode(). As mentioned in Built-in Table-Generating Functions, a UDTF generates zero or more output rows for each input row. A lateral view first applies the UDTF to each row of base table and then joins resulting output rows to the input rows to form a virtual table having the supplied table alias.
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Prior to Hive 0.6.0, lateral view did not support the predicate push-down optimization. In Hive 0.5.0 and earlier, if you used a WHERE clause your query may not have compiled. A workaround was to add set hive.optimize.ppd=false; before your query. The fix was made in Hive 0.6.0; seehttps://issues.apache.org/jira/browse/HIVE-1056: Predicate push down does not work with UDTF‘s.
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From Hive 0.12.0, column aliases can be omitted. In this case, aliases are inherited from field names of StructObjectInspector which is returned from UTDF.
Example
Consider the following base table named pageAds. It has two columns: pageid (name of the page) and adid_list (an array of ads appearing on the page):
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Column name |
Column type |
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pageid |
STRING |
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adid_list |
Array<int> |
An example table with two rows:
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pageid |
adid_list |
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front_page |
[1, 2, 3] |
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contact_page |
[3, 4, 5] |
and the user would like to count the total number of times an ad appears across all pages.
A lateral view with explode() can be used to convert adid_list into separate rows using the query:
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The resulting output will be
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pageid (string) |
adid (int) |
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"front_page" |
1 |
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"front_page" |
2 |
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"front_page" |
3 |
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"contact_page" |
3 |
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"contact_page" |
4 |
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"contact_page" |
5 |
Then in order to count the number of times a particular ad appears, count/group by can be used:
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int adid |
count(1) |
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1 |
1 |
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2 |
1 |
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3 |
2 |
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4 |
1 |
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5 |
1 |
Multiple Lateral Views
A FROM clause can have multiple LATERAL VIEW clauses. Subsequent LATERAL VIEWS can reference columns from any of the tables appearing to the left of the LATERAL VIEW.
For example, the following could be a valid query:
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LATERAL VIEW clauses are applied in the order that they appear. For example with the following base table:
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Array<int> col1 |
Array<string> col2 |
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[1, 2] |
[a", "b", "c"] |
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[3, 4] |
[d", "e", "f"] |
The query:
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Will produce:
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int mycol1 |
Array<string> col2 |
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1 |
[a", "b", "c"] |
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2 |
[a", "b", "c"] |
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3 |
[d", "e", "f"] |
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4 |
[d", "e", "f"] |
A query that adds an additional LATERAL VIEW:
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Will produce:
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int myCol1 |
string myCol2 |
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1 |
"a" |
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1 |
"b" |
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1 |
"c" |
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2 |
"a" |
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2 |
"b" |
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2 |
"c" |
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3 |
"d" |
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3 |
"e" |
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3 |
"f" |
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4 |
"d" |
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4 |
"e" |
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4 |
"f" |
Outer Lateral Views
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Introduced in Hive version 0.12.0
The user can specify the optional OUTER keyword to generate rows even when a LATERAL VIEW usually would not generate a row. This happens when the UDTF used does not generate any rows which happens easily with explode when the column to explode is empty. In this case the source row would never appear in the results. OUTER can be used to prevent that and rows will be generated with NULL values in the columns coming from the UDTF.
For example, the following query returns an empty result:
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But with the OUTER keyword
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it will produce:
238 val_238 NULL
86 val_86 NULL
311 val_311 NULL
27 val_27 NULL
165 val_165 NULL
409 val_409 NULL
255 val_255 NULL
278 val_278 NULL
98 val_98 NULL