Apache Flume Features & Limitations of Apache Flume
As we all know while it comes to transferring the data from source to destination, Apache flume is the best open source data collection service. However, there are many more Flume features we can discuss. So in this blog “Flume Features and limitations” we will discuss all the advantages of Apache Flume. Apart from Flume benefits, there are some Flume disadvantages also. Hence, we will also cover all limitations of Apache Flume.
2. Introduction to Apache Flume
For efficiently collecting, aggregating, and moving large amounts of streaming data into the Hadoop Distributed File System (HDFS) we use Apache Flume. Basically, it is a distributed, reliable, and available service. Moreover, we can say, on the basis of streaming data flows it has a simple and flexible architecture. Likewise, it is robust and faults tolerant in nature. Especially, with tunable reliability mechanisms for failover and recovery.
Learn more about Apache Flume Architecture
If these professionals can make a switch to Big Data, so can you:
3. Flume Features and Limitations
a. Apache Flume Features
There are many core advantages of Apache Flume available. They are:
i. Open source
Apache flume is open source i.e. easily available.
There are many good examples and patterns of how these can be applied, is available in its documentation.
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Apache Flume offers high throughput with lower latency.
It contains a very declarative configuration.
Follow this link, to know more about Flume configuration & Installation
v. Data Flow
In Hadoop environments, Flume works with streaming data sources which are generated continuously. Such as log files.
Generally, Flume looks at the payload such as stream data or event. Also, construct a routing which is apt.
While it comes to maintain Flume, we can say less costly to install, operate and maintain.
viii. Fault Tolerance and Scalable
Apache Flume is highly extensible, reliable, available, horizontally scalable as well as customizable for different sources and sinks. However, that helps in collecting, aggregating and moving a large number of datasets. For example Facebook, Twitter and e-commerce websites.
It is inherently distributed in nature.
x. Reliable Message Delivery
It offers reliable message delivery. Basically, in Flume the transactions are channel-based where two transactions (one sender & one receiver) are maintained for each message.
It gives us a solution which is reliable and distributed and helps us to ingest online streaming data from various sources (network traffic, social media, email messages, log files etc) in HDFS.
xii. Steady Flow
Flume offers a steady flow of data if the read the write rate, between reading and write operations.
Let’s read about Data Transfer from Flume to HDFS in detail
b. Limitations of Flume
As we know if there are advantages, there are also disadvantages. So let’s discuss disadvantages of Apache Flume which are pulling it down on certain aspects. Such as:
i. Weak Ordering Guarantee
While it comes to ordering guarantee, Apache flume is very weak in it.
In many scenarios, Flume does not guarantee that message reaching is unique. However, it is a possibility that duplicate messages might pop in at times.
You must know Apache Flume Use Cases – Future Scope
iii. Low Scalability
There is a slight possibility that for an enterprise, sizing the hardware of a typical Flume can be tricky, and in most cases, it’s trial and error. Hence, its scalability aspect is often low.
iv. Reliability issues
When the choice of backing store is not chosen wisely considering all factors, scalability and reliability are under question.
Hence, in this article “Flume Features and limitations”, we have learned all Apache Flume features as well as limitations of Apache Flume. However, if any query occurs, feel free to ask in the comment section.
See Also- Flume Troubleshooting – Flume Known Issues