Details
This course provides a technical overview of Apache Hadoop. It includes high-level information about concepts, architecture, operation, and uses of the Hortonworks Data Platform (HDP) and the Hadoop ecosystem. The course provides an optional primer for
those who plan to attend a hands-on, instructor-led course.
PREREQUISITES No previous Hadoop or programming knowledge is required. Students will need browser access to the Internet.
TARGET AUDIENCE Data architects, data integration architects, managers, C-level executives, decision makers, technical infrastructure team, and Hadoop administrators or developers who want to understand the fundamentals of Big Data and the Hadoop ecosystem.
FORMAT 100% Lecture/Instructor Discussion
AGENDA SUMMARY Day 1: Hadoop Overview and Demonstrations
OBJECTIVES
• Describe the case for Hadoop • Identify the Hadoop Ecosystem and architecture • Data Management – HDFS, YARN • Data Access – Pig, Hive, HBase, Storm, Solr, Spark • Data Governance & Integration – Falcon, Flume, Sqoop, Kafka, Atlas • Security – Kerberos, Falcon, Knox • Operations – Ambari, Zookeeper, Oozie, Cloudbreak • Observe popular data transformation and processing engines in action: Apache Hive, Apache Pig, Apache Spark • Detail the architecture and features of YARN • Describe backup and recovery options • Describe how to secure Hadoop • Explain the fundamentals of parallel processing • Describe data ingestion options and frameworks for batch and real-time streaming • Detail the HDFS architecture
DEMONSTRATIONS
• Operational Overview with Ambari • Ingesting Data into HDFS • Data Manipulation with Hive • Risk Factor Analysis with Pig • Risk Analysis with Spark • Securing Hive with Ranger
PREREQUISITES No previous Hadoop or programming knowledge is required. Students will need browser access to the Internet.
TARGET AUDIENCE Data architects, data integration architects, managers, C-level executives, decision makers, technical infrastructure team, and Hadoop administrators or developers who want to understand the fundamentals of Big Data and the Hadoop ecosystem.
FORMAT 100% Lecture/Instructor Discussion
AGENDA SUMMARY Day 1: Hadoop Overview and Demonstrations
OBJECTIVES
• Describe the case for Hadoop • Identify the Hadoop Ecosystem and architecture • Data Management – HDFS, YARN • Data Access – Pig, Hive, HBase, Storm, Solr, Spark • Data Governance & Integration – Falcon, Flume, Sqoop, Kafka, Atlas • Security – Kerberos, Falcon, Knox • Operations – Ambari, Zookeeper, Oozie, Cloudbreak • Observe popular data transformation and processing engines in action: Apache Hive, Apache Pig, Apache Spark • Detail the architecture and features of YARN • Describe backup and recovery options • Describe how to secure Hadoop • Explain the fundamentals of parallel processing • Describe data ingestion options and frameworks for batch and real-time streaming • Detail the HDFS architecture
DEMONSTRATIONS
• Operational Overview with Ambari • Ingesting Data into HDFS • Data Manipulation with Hive • Risk Factor Analysis with Pig • Risk Analysis with Spark • Securing Hive with Ranger
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Agilitics Pte. Ltd. is a reknowned Big Data Analytics firm headquartered in Singapore with operations in mulitple countries. They are expert of big data and belive and spreading the knowledging for betterment of the Big Data community and generating bigger and better talent pool for industry.
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