EMR Hadoop Ecosystem for OLTP and Operational Analytics
Question
Allianz Financial Services (AFS) is a banking group offering end-to-end banking and financial solutions in South East Asia through its consumer banking, business banking, Islamic banking, investment finance and stock broking businesses as well as unit trust and asset administration, having served the financial community over the past five decades. AFS launched EMR cluster to support their big data analytics requirements.
AFS is planning to build an application running on EMR which supports both OLTP and operational analytics allowing you to use standard SQL queries and JDBC APIs to work with an Apache HBase backing store.
Also data transfer tool between Amazon S3, Hadoop, HDFS, and RDBMS databases. Which EMR Hadoop ecosystem fulfills the requirements? select 2 options.
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Answer : C,D.
Option A is incorrect -Hue (Hadoop User Experience) is an open-source, web-based, graphical user interface for use with Amazon EMR and Apache Hadoop.
Hue groups together several different Hadoop ecosystem projects into a configurable interface.
Amazon EMR has also added customizations specific to Hue in Amazon EMR.
Hue acts as a front-end for applications that run on your cluster, allowing you to interact with applications using an interface that may be more familiar or user-friendly.
The applications in Hue, such as the Hive and Pig editors, replace the need to log in to the cluster to run scripts interactively using each application's respective shell
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hue.htmlOption B is incorrect -Apache Flink is a streaming dataflow engine that you can use to run real-timestream processing on high-throughput data sources.
Flink supports event time semantics for out-of-order events, exactly-once semantics, backpressure control, and APIs optimized for writing both streaming and batch applications.
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-flink.htmlOption C is correct -Apache Phoenix is used for OLTP and operational analytics, allowing you to use standard SQL queries and JDBC APIs to work with an Apache HBase backing store.
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-phoenix.htmlOption D is correct -Apache Sqoop is a tool for transferring data between Amazon S3, Hadoop, HDFS, and RDBMS databases.
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-sqoop.htmlThe EMR cluster launched by AFS is intended to support their big data analytics requirements. AFS plans to build an application on EMR that will allow them to use standard SQL queries and JDBC APIs to work with an Apache HBase backing store, and also transfer data between Amazon S3, Hadoop, HDFS, and RDBMS databases.
Based on the requirements, the two EMR Hadoop ecosystem options that would fulfill the requirements are:
C. Apache Phoenix: Apache Phoenix is a relational database layer over HBase that allows for standard SQL queries and JDBC APIs to be used to interact with the data stored in HBase. Phoenix is designed to provide a high-performance, low-latency access layer to HBase that enables OLTP and operational analytics.
D. Apache Sqoop: Apache Sqoop is a tool designed to transfer data between Hadoop and structured datastores such as relational databases. Sqoop provides a simple command-line interface that allows for the transfer of large amounts of data between Hadoop and external datastores.
Apache Hue is a web-based interface for Hadoop that provides a GUI for accessing various Hadoop components such as HDFS, MapReduce, and Hive. It does not provide the SQL and JDBC API features required by AFS.
Apache Flink is a distributed stream processing framework that can be used for real-time data processing. It does not provide the SQL and JDBC API features required by AFS.
In conclusion, Apache Phoenix and Apache Sqoop are the two EMR Hadoop ecosystem options that fulfill the requirements of AFS's application for supporting both OLTP and operational analytics with standard SQL queries and JDBC APIs, and data transfer between Amazon S3, Hadoop, HDFS, and RDBMS databases.
