we are trying to replicate an oracle db into hive. We get the queries from oracle and run them in hive. So, we get them in this format:
INSERT INTO schema.table(col1,col2) VALUES ('val','val');
While this query works in Hive directly, when I use spark.sql, I get the following error:
org.apache.spark.sql.catalyst.parser.ParseException:
mismatched input 'emp_id' expecting {'(', 'SELECT', 'FROM', 'VALUES', 'TABLE', 'INSERT', 'MAP', 'REDUCE'}(line 1, pos 20)
== SQL ==
insert into ss.tab(emp_id,firstname,lastname) values ('1','demo','demo')
--------------------^^^
at org.apache.spark.sql.catalyst.parser.ParseException.withCommand(ParseDriver.scala:217)
at org.apache.spark.sql.catalyst.parser.AbstractSqlParser.parse(ParseDriver.scala:114)
at org.apache.spark.sql.execution.SparkSqlParser.parse(SparkSqlParser.scala:48)
at org.apache.spark.sql.catalyst.parser.AbstractSqlParser.parsePlan(ParseDriver.scala:68)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:623)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:691)
at com.datastream.SparkReplicator.insertIntoHive(SparkReplicator.java:20)
at com.datastream.App.main(App.java:67)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:755)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
This error is coming as Spark SQL does not support column lists in the insert statement. so exclude the column list from the insert statement.
below was my hive table:
select * from UDB.emp_details_table;
+---------+-----------+-----------+-------------------+--+
| emp_id | emp_name | emp_dept | emp_joining_date |
+---------+-----------+-----------+-------------------+--+
| 1 | AAA | HR | 2018-12-06 |
| 1 | BBB | HR | 2017-10-26 |
| 2 | XXX | ADMIN | 2018-10-22 |
| 2 | YYY | ADMIN | 2015-10-19 |
| 2 | ZZZ | IT | 2018-05-14 |
| 3 | GGG | HR | 2018-06-30 |
+---------+-----------+-----------+-------------------+--+
here I am inserting record using spark sql through pyspark
df = spark.sql("""insert into UDB.emp_details_table values ('6','VVV','IT','2018-12-18')""");
you could see below that given record has been inserted to my existing hive table.
+---------+-----------+-----------+-------------------+--+
| emp_id | emp_name | emp_dept | emp_joining_date |
+---------+-----------+-----------+-------------------+--+
| 1 | AAA | HR | 2018-12-06 |
| 1 | BBB | HR | 2017-10-26 |
| 2 | XXX | ADMIN | 2018-10-22 |
| 2 | YYY | ADMIN | 2015-10-19 |
| 2 | ZZZ | IT | 2018-05-14 |
| 3 | GGG | HR | 2018-06-30 |
| 6 | VVV | IT | 2018-12-18 |
+---------+-----------+-----------+-------------------+--+
change your spark sql query as :
spark.sql("""insert into ss.tab values ('1','demo','demo')""");
Note: I am using spark 2.3, you need to use hive context in case you are using spark 1.6 version.
Let me know if it works.
来源:https://stackoverflow.com/questions/53812634/spark-sql-issue-with-columns-specified