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 has multiple data sources built out of S3, SQL databases, MongoDB, Redis, RDS, other file systems. AFS is looking for distributed processing framework and programming model that helps you do machine learning, stream processing, or graph analytics using Amazon EMR clusters
Which EMR Hadoop ecosystem fulfills the requirements? select 1 option.

Answer options:

A.Apache Hive
B.Apache HBase
C.pache HCatalog
D.Apache Spark

Answer : D
Option A is incorrect -Hive is an open-source, data warehouse, and analytic package that runs on top of a Hadoop cluster. Hive scripts use an SQL-like language called Hive QL (query language) that abstracts programming models and supports typical data warehouse interactions. Hive enables you to avoid the complexities of writing Tez jobs based on directed acyclic graphs (DAGs) or MapReduce programs in a lower level computer language, such as Java. Hive extends the SQL paradigm by including serialization formats. You can also customize query processing by creating table schema that matches your data, without touching the data itself. In contrast to SQL (which only supports primitive value types such as dates, numbers, and strings), values in Hive tables are structured elements, such as JSON objects, any user-defined data type, or any function written in Java. 
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hive.html
Option B is incorrect - HBase is an open source, non-relational, distributed database developed as part of the Apache Software Foundation`s Hadoop project. HBase runs on top of Hadoop Distributed File System (HDFS) to provide non- relational database capabilities for the Hadoop ecosystem. HBase works seamlessly with Hadoop, sharing its file system and serving as a direct input and output to the MapReduce framework and execution engine. HBase also integrates with Apache Hive, enabling SQL-like queries over HBase tables, joins with Hive-based tables, and support for Java Database Connectivity (JDBC). 
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hbase.html
Option C is incorrect -HCatalog is a tool that allows you to access Hive metastore tables within Pig, Spark SQL, and/or custom MapReduce applications. HCatalog has a REST interface and command line client that allows you to create tables or do other operations. 
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hcatalog.html
Option D is correct - Apache Spark is a distributed processing framework and programming model that helps you do machine learning, stream processing, or graph analytics using Amazon EMR clusters. Similar to Apache Hadoop, Spark is an open-source,distributed processing system commonly used for big data workloads. However, Spark has several notable differences from Hadoop MapReduce. Spark has an optimized directed acyclic graph (DAG) execution engine and actively caches data in-memory, which can boost performance, especially for certain algorithms and interactive queries. 
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-spark.html