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Loading Postgres from Sqoop

PostgreSQL and Hadoop are complementary technologies. PostgreSQL outperforms Hadoop to retrieve small amount of information from multiple tables. Hadoop outperforms PostgreSQL to transform multiple tables into simplfied and aggregated tables. So, how to load PostgreSQL efficiently from Hadoop ?

Sqoop as a bridge

Hadoop stores data on its distributed filesystem: HDFS. At the end of the day, the resulting procecced data is stored into a hdfs table and may need to be loaded into a PosgreSQL table.

Copy is a efficient a robust PostgreSQL bulkloading function allowing to load among from others CSV files. It is way faster than a bunch of parallel prepared insert statements.

ORC is a efficient and compressed Hadoop data format. It is both faster to build and to read compared to CSV files.

As the bridge for Hadoop and relational databases, Sqoop manages all ORC, CSV, COPY and INSERT methodologies. When dealing with PostgreSQL, there is no perfect solution.

Sqoop best approach

There is two different scenario to load PostgreSQL.

structured columns

Sqoop does not allow to use COPY together with ORC tables but only with CSV. It splits them and run multiple COPY statements from each part in parallel from HDFS. The CSV format needs to be defined in the sqoop parameters.

unstructured columns

Text information may contain new lines. In this situation, Sqoop is stuck when it splits the CSV into multiple parts. Yet it is not possible to use the sqoop direct mode, and the parallel inserts is the only way to succeed. By chance, it is not necessar to transform the result as CSV, and it is finally possible to exploit ORC tables as-is.

Writing this post makes me thinking about a potential workaround to load textual CSV from COPY by using only one mapper in this situation. Since COPY is highly optimized it is possible that it won't degrade the performances while making the overall process totally robust.

EDIT:

Indeed, using only one mapper allows to handle multiline CSV. Since COPY is very fast and has been optimized to import dataset into postgreSQL, in the general case, the method can be generalized to any kind of CSV to work in any situation. That's the ultimate way to load PostgreSQL from Hadoop:

sqoop export\
--connect "jdbc:postgresql://<postgres_host>/<postgres_db>"\
--username <postgres_user>\
--password-file file:///home/$USER/.password\
--export-dir /apps/hive/warehouse/<my_db>/<my_csv_table>\
--table <my_postgres_table>\
--columns "id, text_column"\
-m 1\
--direct\
--lines-terminated-by '\n'\
--fields-terminated-by ','\
--input-null-string "\\\\N"\
--input-null-non-string "\\\\N"\
-- --schema <my_schema>

In order to prepare the table ready to be loaded by sqoop, it can be transformed with a hive sql query:

CREATE TABLE <my_db>.<my_csv_table> 
STORED AS textfile  
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
AS
SELECT *
FROM <my_hive_table>
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