SQL LIKE in Spark SQL
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6
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I'm trying to implement a join in Spark SQL using a LIKE condition.
The row I am performing the join on looks like this and is called 'revision':
Table A:
8NXDPVAE
Table B:
[4,8]NXD_V%
Performing the join on SQL server (A.revision LIKE B.revision) works just fine, but when doing the same in Spark SQL, the join returns no rows (if using inner join) or null values for Table B (if using outer join).
This is the query I am running:
val joined = spark.sql("SELECT A.revision, B.revision FROM RAWDATA A LEFT JOIN TPTYPE B ON A.revision LIKE B.revision")
The plan looks like this:
== Physical Plan ==
BroadcastNestedLoopJoin BuildLeft, LeftOuter, revision#15 LIKE revision#282, false
:- BroadcastExchange IdentityBroadcastMode
: +- *Project [revision#15]
: +- *Scan JDBCRelation(RAWDATA) [revision#15] PushedFilters: [EqualTo(bulk_id,2016092419270100198)], ReadSchema: struct<revision>
+- *Scan JDBCRelation(TPTYPE) [revision#282] ReadSchema: struct<revision>
Is it possible to perform a LIKE join like this or am I way off?
sql regex apache-spark apache-spark-sql
edited Nov 12 at 13:49
Community♦
11
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
add a comment |
up vote
6
down vote
favorite
I'm trying to implement a join in Spark SQL using a LIKE condition.
The row I am performing the join on looks like this and is called 'revision':
Table A:
8NXDPVAE
Table B:
[4,8]NXD_V%
Performing the join on SQL server (A.revision LIKE B.revision) works just fine, but when doing the same in Spark SQL, the join returns no rows (if using inner join) or null values for Table B (if using outer join).
This is the query I am running:
val joined = spark.sql("SELECT A.revision, B.revision FROM RAWDATA A LEFT JOIN TPTYPE B ON A.revision LIKE B.revision")
The plan looks like this:
== Physical Plan ==
BroadcastNestedLoopJoin BuildLeft, LeftOuter, revision#15 LIKE revision#282, false
:- BroadcastExchange IdentityBroadcastMode
: +- *Project [revision#15]
: +- *Scan JDBCRelation(RAWDATA) [revision#15] PushedFilters: [EqualTo(bulk_id,2016092419270100198)], ReadSchema: struct<revision>
+- *Scan JDBCRelation(TPTYPE) [revision#282] ReadSchema: struct<revision>
Is it possible to perform a LIKE join like this or am I way off?
sql regex apache-spark apache-spark-sql
edited Nov 12 at 13:49
Community♦
11
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
add a comment |
up vote
6
down vote
favorite
up vote
6
down vote
favorite
I'm trying to implement a join in Spark SQL using a LIKE condition.
The row I am performing the join on looks like this and is called 'revision':
Table A:
8NXDPVAE
Table B:
[4,8]NXD_V%
Performing the join on SQL server (A.revision LIKE B.revision) works just fine, but when doing the same in Spark SQL, the join returns no rows (if using inner join) or null values for Table B (if using outer join).
This is the query I am running:
val joined = spark.sql("SELECT A.revision, B.revision FROM RAWDATA A LEFT JOIN TPTYPE B ON A.revision LIKE B.revision")
The plan looks like this:
== Physical Plan ==
BroadcastNestedLoopJoin BuildLeft, LeftOuter, revision#15 LIKE revision#282, false
:- BroadcastExchange IdentityBroadcastMode
: +- *Project [revision#15]
: +- *Scan JDBCRelation(RAWDATA) [revision#15] PushedFilters: [EqualTo(bulk_id,2016092419270100198)], ReadSchema: struct<revision>
+- *Scan JDBCRelation(TPTYPE) [revision#282] ReadSchema: struct<revision>
Is it possible to perform a LIKE join like this or am I way off?
sql regex apache-spark apache-spark-sql
edited Nov 12 at 13:49
Community♦
11
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
I'm trying to implement a join in Spark SQL using a LIKE condition.
The row I am performing the join on looks like this and is called 'revision':
Table A:
8NXDPVAE
Table B:
[4,8]NXD_V%
Performing the join on SQL server (A.revision LIKE B.revision) works just fine, but when doing the same in Spark SQL, the join returns no rows (if using inner join) or null values for Table B (if using outer join).
This is the query I am running:
val joined = spark.sql("SELECT A.revision, B.revision FROM RAWDATA A LEFT JOIN TPTYPE B ON A.revision LIKE B.revision")
The plan looks like this:
== Physical Plan ==
BroadcastNestedLoopJoin BuildLeft, LeftOuter, revision#15 LIKE revision#282, false
:- BroadcastExchange IdentityBroadcastMode
: +- *Project [revision#15]
: +- *Scan JDBCRelation(RAWDATA) [revision#15] PushedFilters: [EqualTo(bulk_id,2016092419270100198)], ReadSchema: struct<revision>
+- *Scan JDBCRelation(TPTYPE) [revision#282] ReadSchema: struct<revision>
Is it possible to perform a LIKE join like this or am I way off?
sql regex apache-spark apache-spark-sql
sql regex apache-spark apache-spark-sql
edited Nov 12 at 13:49
Community♦
11
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
edited Nov 12 at 13:49
Community♦
11
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
edited Nov 12 at 13:49
Community♦
11
edited Nov 12 at 13:49
Community♦
11
edited Nov 12 at 13:49
Community♦
11
11
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
asked Nov 6 '16 at 20:38
Dan Markhasin
2181413
2181413
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
up vote
7
down vote
accepted
You are only a little bit off. Spark SQL and Hive follow SQL standard conventions where LIKE operator accepts only two special characters:
_(underscore) - which matches an arbitrary character.
%(percent) - which matches an arbitrary sequence of characters.
Square brackets have no special meaning and [4,8] matches only a [4,8] literal:
spark.sql("SELECT '[4,8]' LIKE '[4,8]'").show
+----------------+
|[4,8] LIKE [4,8]|
+----------------+
| true|
+----------------+
To match complex patterns you can use RLIKE operator which suports Java regular expressions:
spark.sql("SELECT '8NXDPVAE' RLIKE '^[4,8]NXD.V.*$'").show
+-----------------------------+
|8NXDPVAE RLIKE ^[4,8]NXD.V.*$|
+-----------------------------+
| true|
+-----------------------------+
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
7
down vote
accepted
You are only a little bit off. Spark SQL and Hive follow SQL standard conventions where LIKE operator accepts only two special characters:
_(underscore) - which matches an arbitrary character.
%(percent) - which matches an arbitrary sequence of characters.
Square brackets have no special meaning and [4,8] matches only a [4,8] literal:
spark.sql("SELECT '[4,8]' LIKE '[4,8]'").show
+----------------+
|[4,8] LIKE [4,8]|
+----------------+
| true|
+----------------+
To match complex patterns you can use RLIKE operator which suports Java regular expressions:
spark.sql("SELECT '8NXDPVAE' RLIKE '^[4,8]NXD.V.*$'").show
+-----------------------------+
|8NXDPVAE RLIKE ^[4,8]NXD.V.*$|
+-----------------------------+
| true|
+-----------------------------+
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
add a comment |
up vote
7
down vote
accepted
You are only a little bit off. Spark SQL and Hive follow SQL standard conventions where LIKE operator accepts only two special characters:
_(underscore) - which matches an arbitrary character.
%(percent) - which matches an arbitrary sequence of characters.
Square brackets have no special meaning and [4,8] matches only a [4,8] literal:
spark.sql("SELECT '[4,8]' LIKE '[4,8]'").show
+----------------+
|[4,8] LIKE [4,8]|
+----------------+
| true|
+----------------+
To match complex patterns you can use RLIKE operator which suports Java regular expressions:
spark.sql("SELECT '8NXDPVAE' RLIKE '^[4,8]NXD.V.*$'").show
+-----------------------------+
|8NXDPVAE RLIKE ^[4,8]NXD.V.*$|
+-----------------------------+
| true|
+-----------------------------+
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
add a comment |
up vote
7
down vote
accepted
up vote
7
down vote
accepted
You are only a little bit off. Spark SQL and Hive follow SQL standard conventions where LIKE operator accepts only two special characters:
_(underscore) - which matches an arbitrary character.
%(percent) - which matches an arbitrary sequence of characters.
Square brackets have no special meaning and [4,8] matches only a [4,8] literal:
spark.sql("SELECT '[4,8]' LIKE '[4,8]'").show
+----------------+
|[4,8] LIKE [4,8]|
+----------------+
| true|
+----------------+
To match complex patterns you can use RLIKE operator which suports Java regular expressions:
spark.sql("SELECT '8NXDPVAE' RLIKE '^[4,8]NXD.V.*$'").show
+-----------------------------+
|8NXDPVAE RLIKE ^[4,8]NXD.V.*$|
+-----------------------------+
| true|
+-----------------------------+
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
You are only a little bit off. Spark SQL and Hive follow SQL standard conventions where LIKE operator accepts only two special characters:
_(underscore) - which matches an arbitrary character.
%(percent) - which matches an arbitrary sequence of characters.
Square brackets have no special meaning and [4,8] matches only a [4,8] literal:
spark.sql("SELECT '[4,8]' LIKE '[4,8]'").show
+----------------+
|[4,8] LIKE [4,8]|
+----------------+
| true|
+----------------+
To match complex patterns you can use RLIKE operator which suports Java regular expressions:
spark.sql("SELECT '8NXDPVAE' RLIKE '^[4,8]NXD.V.*$'").show
+-----------------------------+
|8NXDPVAE RLIKE ^[4,8]NXD.V.*$|
+-----------------------------+
| true|
+-----------------------------+
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
answered Nov 6 '16 at 21:25
user6910411
32.4k86793
32.4k86793
add a comment |
add a comment |
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