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What is the main use case of Flume?

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What is the main use case of Flume?

Apache Flume is an open-source tool that is used for collecting and transferring streaming data from the external sources to the terminal repository such as HBase, HDFS, etc. With Apache Flume we can transfer the real-time logs generated by web servers to the HDFS.

How do you integrate Flume with Kafka?

As a consumer Here is the diagram for both Producer and Consumer. And how to integrate Kafka with Flume to publish data to Kafka topic as well as write data to HDFS Storage.

What is flume and Kafka?

Apache Kafka is a distributed data store optimized for ingesting and processing streaming data in real-time. 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.

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What is Flume used for in Hadoop?

Apache Flume is a tool/service/data ingestion mechanism for collecting aggregating and transporting large amounts of streaming data such as log data, events (etc…) from various webserves to a centralized data store.

Which of the following functions does Flume support?

Explanation: Flume is used for efficiently collecting, aggregating, and moving large amounts of streaming event data.

What is difference between flume and sqoop?

Sqoop is used for bulk transfer of data between Hadoop and relational databases and supports both import and export of data. Flume is used for collecting and transferring large quantities of data to a centralized data store.

Can flume collect server logs to Kafka?

Flume acquisition system structure There are many kinds of data sources: they can come from directory, HTTP, Kafka, etc. flume provides the source component to collect data sources.

How connect Kafka to HDFS?

Kafka-Connect with HDFS on a distributed system.

  1. First pushed some data as JSON format in Kafka using a producer.
  2. Download kafka-connect-hdfs and kafka-connect-storage-common and do git checkout tags/v5.3.1 (Use the confluent version according to your kafka version from here.
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What is flume and sqoop?

What is the difference between Flume and Kafka?

Flume and Kafka are actually two quite different products. Kafka is a general purpose publish-subscribe model messaging system, which offers strong durability, scalability and fault-tolerance support. It is not specifically designed for Hadoop.

What is the most common use case for Kafka?

So its common use case is to act as a data pipeline to ingest data into Hadoop. Image taken from https://blogs.apache.org/flume/entry/flume_ng_architecture. Compared to Flume, Kafka wins on the its superb scalability and messsage durablity. Kafka is very scalable.

Is Kafka source and HDFS Sink supported by Apache Flume?

However, the Kafka Source and HDFS Sink are built-in supported by Apache Flume. Therefore, they will help us in reducing our effort. In next post, I’d like to share how to use other Apache Flume Sources and Sinks.

How to implement Apache Kafka in real-time processing?

We can implement them easily by using Apache Kafka Connect, tools like Apache Flume with appropriate Flume Sources and Flume Kafka Sink, or simply write some custom Apache Kafka consumers and producers. When data in Apache Kafka, it is easy for real-time processing frameworks like Apache Spark or Apache Storm to consume and process in real-time.

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