Apache Flume Use Cases – Future Scope in Flume
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1. Objective – Use Cases of Flume
As we know while it comes to handling the data flowing to/from the relational database and fast-moving unstructured data we use Flume. However, there are many more cases where we can use Apache Flume. Hence, in this article, we will learn all the possible Apache Flume use cases. But before Flume use cases, we will also learn its brief introduction to understand it well.
So, let’s start exploring Flume Use Cases.
2. What is Apache Flume?
While it comes to collect, aggregate and transports large amounts of streaming data like log files, events, etc., from a number of different sources to a centralized data store (say Hadoop Distributed File System – HDFS) we use Apache Flume.
In addition, it is highly distributed, reliable, and configurable tool. To be more specific, the major purpose of its design is to collect streaming data (log data) from various web servers to HDFS.
Follow this link to know more about Apache Flume Features & Limitations
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3. Flume Use Cases
Let’s discuss all the possible Apache Flume Use Cases.
i. While we want to acquire data from a variety of source and store into Hadoop system, we use Apache Flume.
ii. Whenever we need to handle high-velocity and high-volume data into Hadoop system, we go for Apache Flume.
iii. It also helps in the reliable delivery of data to the destination.
iv. When the velocity and volume of data increases, Flume turned as a scalable solution that can run quite easily just by adding more machine to it.
v. Without incurring any downtime Flume dynamically configures the various components of the Flume Architecture.
vi. We can achieve a single point of contact with Flume, for all the various configurations based on which the overall architecture is functioning.
Let’s read about Apache Flume Installation
vii. While it comes to real-time streaming of data we use Apache Flume.
viii. Efficient collection of the log data and ingestion into a centralized store (HDFS, HBase), from multiple servers, we use Flume.
ix. We can collect the data from multiple servers in real-time as well as in batch mode, with the help of Flume.
x. we can easily import Huge volumes of event data generated and analyzed in real-time by social media websites like Facebook and Twitter and various e-commerce websites such as Amazon and Flipkart.
xi. It is possible to collect data from a large set of sources and then move them to multiple destinations with Flume.
xii. Flume also supports Multi-hop flows, fan-in fan-out flows, and contextual routing.
xiii. Moreover, while we have multiple web applications server running, generating logs or us have to move logs at very fast speed to HDFS, we use Apache Flume.
xiv. Also, we use Flume to do a sentiment analysis or to download using crawlers various data from the twitter and then move this data to HDFS.
xv. By using interceptors, in Flume, we can process data in-flight.
xvi. For data masking or filtering, Flume can be very useful.
xvii. It is possible to scale it horizontally.
So, this was all in Flume Use Cases. Hope you like our explanation.