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author | Justin Pihony <justin.pihony@gmail.com> | 2016-09-26 09:54:22 +0100 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-09-26 09:54:22 +0100 |
commit | 50b89d05b7bffc212cc9b9ae6e0bca7cb90b9c77 (patch) | |
tree | 004018c95e9fedc204d683c210af79ac43bd4212 /examples/src/main/python/sql | |
parent | ac65139be96dbf87402b9a85729a93afd3c6ff17 (diff) | |
download | spark-50b89d05b7bffc212cc9b9ae6e0bca7cb90b9c77.tar.gz spark-50b89d05b7bffc212cc9b9ae6e0bca7cb90b9c77.tar.bz2 spark-50b89d05b7bffc212cc9b9ae6e0bca7cb90b9c77.zip |
[SPARK-14525][SQL] Make DataFrameWrite.save work for jdbc
## What changes were proposed in this pull request?
This change modifies the implementation of DataFrameWriter.save such that it works with jdbc, and the call to jdbc merely delegates to save.
## How was this patch tested?
This was tested via unit tests in the JDBCWriteSuite, of which I added one new test to cover this scenario.
## Additional details
rxin This seems to have been most recently touched by you and was also commented on in the JIRA.
This contribution is my original work and I license the work to the project under the project's open source license.
Author: Justin Pihony <justin.pihony@gmail.com>
Author: Justin Pihony <justin.pihony@typesafe.com>
Closes #12601 from JustinPihony/jdbc_reconciliation.
Diffstat (limited to 'examples/src/main/python/sql')
-rw-r--r-- | examples/src/main/python/sql/datasource.py | 19 |
1 files changed, 19 insertions, 0 deletions
diff --git a/examples/src/main/python/sql/datasource.py b/examples/src/main/python/sql/datasource.py index b36c901d2b..e9aa9d9ac2 100644 --- a/examples/src/main/python/sql/datasource.py +++ b/examples/src/main/python/sql/datasource.py @@ -143,6 +143,8 @@ def json_dataset_example(spark): def jdbc_dataset_example(spark): # $example on:jdbc_dataset$ + # Note: JDBC loading and saving can be achieved via either the load/save or jdbc methods + # Loading data from a JDBC source jdbcDF = spark.read \ .format("jdbc") \ .option("url", "jdbc:postgresql:dbserver") \ @@ -150,6 +152,23 @@ def jdbc_dataset_example(spark): .option("user", "username") \ .option("password", "password") \ .load() + + jdbcDF2 = spark.read \ + .jdbc("jdbc:postgresql:dbserver", "schema.tablename", + properties={"user": "username", "password": "password"}) + + # Saving data to a JDBC source + jdbcDF.write \ + .format("jdbc") \ + .option("url", "jdbc:postgresql:dbserver") \ + .option("dbtable", "schema.tablename") \ + .option("user", "username") \ + .option("password", "password") \ + .save() + + jdbcDF2.write \ + .jdbc("jdbc:postgresql:dbserver", "schema.tablename", + properties={"user": "username", "password": "password"}) # $example off:jdbc_dataset$ |