oracle goldengate and apache kafka: a deep dive into real-time data streaming
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Michael Rainey | Oracle OpenWorld 2016
Oracle GoldenGate and Apache Kafka: A Deep Dive Into Real-Time Data Streaming
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Introduction
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• Michael Rainey - Data Integration Lead - Oracle Data Integration expertise - Blog: http://ritt.md/mRainey - Oracle ACE Director
@mRainey
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About Rittman Mead
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•World’s leading specialist partner for technical excellence, solutions delivery and innovation in Oracle Data Integration, Business Intelligence, Analytics and Big Data
•Providing our customers targeted expertise; we are a company that doesn’t try to do everything… only what we excel at
•70+ consultants worldwide including 1 Oracle ACE Director and 2 Oracle ACEs, offering training courses, global services, and consulting
•Founded on the values of collaboration, learning, integrity and getting things done
Unlock the potential of your organization’s data
•Comprehensive service portfolio designed to support the full lifecycle of any analytics solution
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Example - Marketing
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• Financial data stored in RDBMS• Social media data, web logs, Google analytics, etc all in
various formats• Bring it all together for analysis ‣ Marketing campaign effect on sales
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Relational Data Replication - Oracle GoldenGate
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Streaming Data - Apache Kafka
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“Publish-subscribe messaging rethought as a distributed commit log”
Image source: kafka.apache.org/
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Streaming Data - Apache Kafka
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Image source: kafka.apache.org/
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Kafka - How is it used?
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• Pure Event Streams• System Metrics• Derived Streams• Hadoop Data Loads / Data Publishing• Application Logs• Database Changes- Log Compaction - Data cleansing
Image source: confluent.io
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Kafka - How is it used?
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• Pure Event Streams• System Metrics• Derived Streams• Hadoop Data Loads / Data Publishing• Application Logs• Database Changes- Log Compaction - Data cleansing
Image source: confluent.io
XO
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A simple example…
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One view of the Oracle Data Integrator logs• ODI session logs - stored in the repository
database• ODI Agent logs - text files
To see the full picture of your ODI environment, they must be combined
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Steps to extract from the database
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• Prepare the database • Setup GoldenGate for Oracle Database- Install and configure • Setup Manager, Extract and Pump parameter files• Add Extract and Pump process groups• Start the Extract and Pump processes
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Prepare the Database - OGG User Permissions
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Prepare the Database - Logging Settings
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• Enable supplemental logging
• Set GoldenGate Replication parameter
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Stream ODI Agent Logs to Kafka via Logstash
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• Application log processing is a standard use for Kafka
• Logstash- Part of the Elastic (formerly ELK) stack - Robin Moffatt’s post—> http://ritt.md/kafka-elk - Producer configuration for Kafka
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Logstash to Kafka - Setup and Startup
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• Startup Zookeeper- Elects controller broker - Tracks brokers and topic config - Manages access control and quotas • Set Kafka server.properties- Broker ID - Number of partitions - Log retention period - Zookeeper connection • Start Kafka
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Setup Logstash Configuration File
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• Configuration File - logstash-odiagent-kafka-producer.conf
• Start Logstash
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ODI Agent Logs to Kafka!
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• Start the Kafka Console Consumer - delivered with Kafka
• Start the ODI Agent
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Oracle GoldenGate for Big Data
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• Kafka - one of many handlers- HDFS, HBase, Flume, Hive • Pluggable Formatters- Convert trail file transactions to alternate format - Avro, delimited text, JSON, XML • Metadata Provider- Handles mapping of source to target columns that differ in structure/name - Similar to SOURCEDEF file in GoldenGate - Avro or Hive
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Oracle GoldenGate for Big Data - Kafka Handler Setup
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• Standard GoldenGate Extract / Pump processes- Remember, no change here • Replicat for Java parameter file & process group• Kakfa Handler configuration• Kafka Producer properties- Note: Kafka 0.9.0+ now certified with GoldenGate for Big Data
12.2.1.1
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Another approach…
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• Kafka Connect Handler (Open Source)- java.net/downloads/oracledi/GoldenGate - Uses the Kafka Connect framework - Can integrate with Confluent Platform & Schema Registry - Tables = Topics • Differences?- OGG for Big Data Kafka Handler uses pluggable formatters - Kafka Connect Handler builds up schemas and structs via the Kafka
Connect API
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Oracle GoldenGate for Big Data - Prerequisites
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• Zookeeper & Kafka up and running• Add topic to broker up front vs dynamically- Option to create a topic per table (OGG for Big Data 12.2.0.1.1) • Kafka Handler must have access to broker server• Kafka libraries must match Kafka version
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GoldenGate and Kafka - Kafka Handler Properties
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Properties describe how communication between the GoldenGate adapter and Kafka will occur
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GoldenGate and Kafka - Kafka Handler Properties
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• gg.handlerlist = kafkahandler• gg.handler.kafkahandler.type = kafka• gg.handler.kafkahandler.KafkaProducerConfigFile = kafka_producer.properties• gg.handler.kafkahandler.TopicName = odirepo- Kafka topic name • gg.handler.kafkahandler.format = xml | delimitedtext | json | avro_row | avro_op- Pluggable Formatter - Avro recommended for Kafka… • gg.handler.kafkahandler.BlockingSend = true | false - true - synchronous (wait for acknowledgement before sending next message)• gg.handler.kafkahandler.mode = tx | op- Transaction vs Operation mode
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GoldenGate and Kafka - Kafka Handler Properties
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• goldengate.userexit.timestamp = utc• goldengate.userexit.writers = javawriter• javawriter.stats.display = TRUE• javawriter.stats.full = TRUE• gg.log = log4j• gg.log.level = INFO• gg.report.time = 30sec• gg.classpath = dirprm/:/u01/kafka/kafka_2.10-0.8.2.1/libs/*:- Location of the Kafka libraries• javawriter.bootoptions = -Xmx512m -Xms32m -Djava.class.path=ggjava/ggjava.jar
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GoldenGate and Kafka - One Topic Per Table
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• gg.handler.kafkahandler.topicPartitioning = table - Option to split schema into one topic per table- Topics can be created dynamically• gg.handler.kafkahandler.mode = op - Operation mode required to track individual table operations
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GoldenGate and Kafka - Kafka Producer Configuration
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• Access to the Kafka producer configuration parameters
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GoldenGate and Kafka - Startup
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• Create a topic in Kakfa (or one per table)
• Add Replicat process group to GoldenGate on target
• Start Kafka console consumer
• Start GoldenGate extract/pump on source, replicat on target
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Schemas
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• Schema automatically created - Stored in <ogg_home>/dirdef directory - Based on gg.handler.kafkahandler.format setting
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Schemas
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• Schema automatically created - Stored in <ogg_home>/dirdef directory - Based on gg.handler.kafkahandler.format setting
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Schemas
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• Schema automatically created - Stored in <ogg_home>/dirdef directory - Based on gg.handler.kafkahandler.format setting
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GoldenGate Big Data Adapter - What to Think About
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• GoldenGate might be a single point of failure - Kafka is a fault-tolerant, distributed system • Source transactions may end up larger than expected - max.request.size • Performance considerations- batch.size and linger.ms
• higher values = increased latency, better throughput - BlockingSend = false and Mode = tx - GROUPTRANSOPS • Monitoring- Confluent? Custom?
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Why GoldenGate with Kafka?
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• GoldenGate- …is non-invasive - …has checkpoints for recovery - …moves data quickly - …is easy to setup
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Data Integration Architecture - Kafka throughout
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