The component that deals with ingesting streaming data into Hadoop is Flume.

Here's a step-by-step explanation:

1. Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store.

2. Its main goal is to deliver data from applications to Apache Hadoop's HDFS.

3. It has a simple and flexible architecture based on streaming data flows; and it is robust and fault tolerant with tunable reliability mechanisms for failover and recovery.

4. Therefore, among the options given, Flume is the one that deals with ingesting streaming data into Hadoop.

Note: Kafka is also a tool for handling real-time data feeds with a focus on high-throughput, but it's not specifically designed for Hadoop, even though it can be used with it.

Question

The component that deals with ingesting streaming data into Hadoop is Flume.

Here's a step-by-step explanation:

1. Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store.

2. Its main goal is to deliver data from applications to Apache Hadoop's HDFS.

3. It has a simple and flexible architecture based on streaming data flows; and it is robust and fault tolerant with tunable reliability mechanisms for failover and recovery.

4. Therefore, among the options given, Flume is the one that deals with ingesting streaming data into Hadoop.

Note: Kafka is also a tool for handling real-time data feeds with a focus on high-throughput, but it's not specifically designed for Hadoop, even though it can be used with it.

Knowee AI · Accepted Answer

The component that deals with ingesting streaming data into Hadoop is Flume.

Here's a step-by-step explanation:

1. Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store.

2. Its main goal is to deliver data from applications to Apache Hadoop's HDFS.

3. It has a simple and flexible architecture based on streaming data flows; and it is robust and fault tolerant with tunable reliability mechanisms for failover and recovery.

4. Therefore, among the options given, Flume is the one that deals with ingesting streaming data into Hadoop.

Note: Kafka is also a tool for handling real-time data feeds with a focus on high-throughput, but it's not specifically designed for Hadoop, even though it can be used with it.

Which of the below component deals with ingesting streaming data into Hadoop?FlumeOozieHive Kafka

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