Change Data Capture Using Apache NiFi
Capturing all changes from a relational database with Apache NiFi is very easy and explained. CDC is a common use case for extracting transactional data in a streaming manner to populate a datawarehouse or datalake in Hadoop.
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- Download HDP Sandbox
- MySQL database (Should already be present in the sandbox)
- NiFi 0.6 or later (Download and install a new version of NIFI or use Ambari to install NIFI in the sandbox)
MySQL Setup (Source Database)
In this setup, we will create a table in MySQL tables and create a few triggers on the tables to emulate transactions.
- These triggers will find out if the change introduced was an insert or an update
- It will also update the time stamp on the updated/inserted row. (This is very important as NiFi will be polling on this column to extract changes based on the time stamp.)
unix> mysql –u root –p unix>Enter password: mysql> mysql> create database test_cdc; mysql> create user 'test_cdc'@'localhost' identified by 'test_cdc'; mysql> GRANT ALL PRIVILEGES ON *.* TO 'test_CDC'@'%' IDENTIFIED BY 'test_CDC' WITH GRANT OPTION; mysql>Flush Privileges mysql> exit; unix> mysql –u test_cdc –p test_cdc mysql>create table CDC_TEST ( Column_A int, Column_B text, Created_date datetime, INFORMATION text );
Create Triggers in MySQL:
mysql> create trigger CDC_insert before insert on cdc_test for each row set NEW.created_date =NOW() , NEW.information = 'INSERT'; mysql> create trigger CDC_UPDATE before update on cdc_test for each row set NEW.created_date = NOW() , NEW.information = 'UPDATE';
Hive Setup (Destination Database)
In Hive, we have created an external table, with the exact same data structure as MySQL table, NiFi would be used to capture changes from the source and insert them into the Hive table.
Using AMBARI Hive view or from HIVE CLI create the following table in the hive default database.
I have used hive cli to create the table:
Unix> hive Hive> create external table HIVE_TEST_CDC ( COLUMN_A int , COLUMN_B string, CREATED_DATE string, INFORMATION string) stored as avro location '/test-nifi/CDC/'
Note: I am not including how to create Managed Hive table with ORC format, that would be covered in a different article.
This is a simple NIFI setup, the queryDatabase table processor is only available as part of default processors from version 0.6 of NiFi.
It's very intuitive:
The main things to configure is DBCPConnection Pool and Maximum-value Columns.
Please choose this to be the date-time stamp column that could be a cumulative change-management column.
This is the only limitation with this processor as it is not a true CDC and relies on one column. If the data is reloaded into the column with older data the data will not be replicated into HDFS or any other destination.
This processor does not rely on Transactional logs or redo logs like Attunity or Oracle Goldengate. For a complete solution for CDC please use Attunity or Oracle Goldengate solutions.
configure the Hadoop Core-site.xml and hdfs-site.xml and destination HDFS directory in this case it is:
Make sure this directory is present in HDFS otherwise create it using the following command.
Unix> hadoop fs –mkdir –p /test-nifi/CDC
Make sure all the processors are running in NiFi:
Run a bunch of insert statements on MySQL database.
mysql –u test_cdc –p
At the MySQL CLI, run the following inserts:
insert into cdc_test values (3, ‘cdc3’, null, null); insert into cdc_test values (4, ‘cdc3’, null, null); insert into cdc_test values (5, ‘cdc3’, null, null); insert into cdc_test values (6, ‘cdc3’, null, null); insert into cdc_test values (7, ‘cdc3’, null, null); insert into cdc_test values (8, ‘cdc3’, null, null); insert into cdc_test values (9, ‘cdc3’, null, null); insert into cdc_test values (10, ‘cdc3’, null, null); insert into cdc_test values (11, ‘cdc3’, null, null); insert into cdc_test values (12, ‘cdc3’, null, null); insert into cdc_test values (13, ‘cdc3’, null, null);
Select * from cdc_test
Go to Hive using CLI and check if the records were transferred over using NiFi.
Hive> select * from hive_test_cdc
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