{"id":8514,"date":"2018-02-19T05:16:55","date_gmt":"2018-02-19T05:16:55","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=8514"},"modified":"2021-05-09T13:08:34","modified_gmt":"2021-05-09T07:38:34","slug":"flume-features-limitations","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/flume-features-limitations\/","title":{"rendered":"Apache Flume Features & Limitations of Apache Flume"},"content":{"rendered":"

The article enlists various features of Flume and limitations. It explains various Flume features like open-source, scalability, reliability, recoverability, streaming, data flows, and so on. The article also enlisted Flume limitations like weak ordering sequence, low scalability, etc.<\/p>\n

Let us first see a short introduction to Apache Flume.<\/p>\n

Introduction to Apache Flume<\/h2>\n

Apache Flume is a distributed system for collecting, aggregating, and transferring data from external sources like Twitter, Facebook, web servers to the central repository like HDFS.<\/p>\n

It is mainly for loading log data from different sources to Hadoop HDFS. Apache Flume is a highly robust and available service. It is extensible, fault-tolerant, and scalable.<\/p>\n

Let us now study the different features of Apache Flume.<\/p>\n

Features of Apache Flume<\/h2>\n

\"apache<\/a><\/p>\n

1. Open-source<\/h3>\n

Apache Flume is an open-source distributed system. So it is available free of cost.<\/p>\n

2. Data flow<\/h3>\n

Apache Flume allows its users to build multi-hop, fan-in, and fan-out flows. It also allows for contextual routing as well as backup routes (fail-over) for the failed hops.<\/p>\n

3. Reliability<\/h3>\n

In apache flume, the sources transfer events through the channel. The flume source puts events in the channel which are then consumed by the sink. The sink transfers the event to the next agent or to the terminal repository (like HDFS).<\/p>\n

The events in the flume channel are removed only when they are stored in the next agent channel or in the terminal repository.<\/p>\n

In this way, the single-hop message delivery semantics in Apache Flume caters to end-to-end reliability of the flow. Flume uses a transactional approach for guaranteeing reliable delivery of the flume events.<\/p>\n

4. Recoverability<\/h3>\n

The flume events are staged in a flume channel on each flume agent. This manages recovery from failure. Also, Apache Flume supports a durable File channel. File channels can be backed by the local file system.<\/p>\n

5. Steady flow<\/h3>\n

Apache Flume offers steady data flow between reading and writes operations. When the rate at which data is coming exceeds the rate of writing data to the destination, then Apache Flume acts as a mediator between the data producers and the centralized stores. Thus offers a steady flow of data between them.<\/p>\n

6. Latency<\/h3>\n

Apache Flume caters to high throughput with lower latency.<\/p>\n

7. Ease of use<\/h3>\n

With Flume, we can ingest the stream data from multiple web servers and store them to any of the centralized stores such as HBase, Hadoop HDFS, etc.<\/p>\n

8. Reliable message delivery<\/h3>\n

All the transactions in Apache Flume are channel-based. For each message, two transactions are there – one for the sender and one for the receiver. This ensures reliable message delivery.<\/p>\n

9. Import of Huge volumes of data<\/h3>\n

Along with the log files, Apache Flume can also be used for importing huge volumes of data produced by e-commerce sites like Flipkart, Amazon, and networking sites like Twitter, Facebook.<\/p>\n

10. Support for varieties of Sources and Sinks<\/h3>\n

Apache Flume supports a wide range of sources and sinks.<\/p>\n

11. Streaming<\/h3>\n

Apache Flume gives us a reliable solution that helps us ingesting online streaming data from different sources (such as email messages, network traffic, log files, social media, etc) in HDFS.<\/p>\n

12. Fault-tolerant and scalable<\/h3>\n

Flume is an extensible, reliable, highly available, and horizontally scalable system. It is customizable for different types of sources and sinks.<\/p>\n

13. Inexpensive<\/h3>\n

It is an inexpensive system. It is less costly to install and operate. Its maintenance is very economical.<\/p>\n

14. Configuration<\/h3>\n

Apache Flume contains a very declarative configuration.<\/p>\n

15. Documentation<\/h3>\n

Flume provides complete documentation with many good examples and patterns which helps its user to learn how Flume can be used and configured.<\/p>\n

Limitations of Apache Flume<\/h2>\n

\"limitations<\/a><\/p>\n

Some of the limitations of Apache Flume are:<\/p>\n

1. Weak ordering guarantee<\/h3>\n

Apache Flume offers weaker guarantees than the other systems such as message queues in the event of moving data more quickly and for enabling cheaper fault tolerance. In Apache Flume\u2019s end-to-end reliability mode, the flume events are delivered at least once, but with zero ordering guarantees.<\/p>\n

2. Duplicacy<\/h3>\n

Apache Flume does not guarantee that the messages reaching are 100% unique. In many scenarios, the duplicate messages might pop in.<\/p>\n

3. Low scalability<\/h3>\n

Flume scalability is often low because for any businesses, sizing the hardware of a typical Apache Flume may be tricky, and in most of the cases, it is trial and error. Due to this, Flume scalability aspect is often under the lens.<\/p>\n

4. Reliability issue<\/h3>\n

The throughput that Apache Flume can handle depends highly upon the backing store of the channel. So, if the backing store is not chosen wisely, then there may be scalability and reliability issues.<\/p>\n

5. Complex topology<\/h3>\n

It has complex topology and reconfiguration is challenging.<\/p>\n

Despite its disadvantages, Flume’s advantages outweigh its disadvantages.<\/p>\n

Summary<\/h2>\n

In short, we can say that Apache Flume is an open-source distributed system for ingesting online stream data from different sources to Hadoop HDFS or HBase. It is a highly available, reliable, and easy to use the system.<\/p>\n

Apache Flume provides support for different sources and sinks. Apache Flume caters to high throughput with lower latency. Despite its disadvantages, Flume’s advantages outweigh its disadvantages.<\/p>\n","protected":false},"excerpt":{"rendered":"

The article enlists various features of Flume and limitations. It explains various Flume features like open-source, scalability, reliability, recoverability, streaming, data flows, and so on. The article also enlisted Flume limitations like weak ordering...<\/p>\n","protected":false},"author":6,"featured_media":78361,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[316,763,766,773,1730,3935,4574,4593,4818,8240,8245],"class_list":["post-8514","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-flume","tag-advantages-of-apache-flume","tag-apache-flume-advantages","tag-apache-flume-benefits","tag-apache-flume-limitations","tag-benefits-of-apache-flume","tag-disadvantages-of-apache-flume","tag-features-of-apache-flume","tag-features-of-flume","tag-flume-features-and-limitations","tag-limitations-of-apache-flume","tag-limitations-of-flume"],"yoast_head":"\nApache Flume Features & Limitations of Apache Flume - DataFlair<\/title>\n<meta name=\"description\" content=\"Apache Flume Features, Open source, Latency, Fault Tolerance & Scalable,Streaming,Limitations of Flume, Weak Ordering Guarantee, Duplicacy, Low Scalability,\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/flume-features-limitations\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apache Flume Features & Limitations of Apache Flume - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Apache Flume Features, Open source, Latency, Fault Tolerance & Scalable,Streaming,Limitations of Flume, Weak Ordering Guarantee, Duplicacy, Low Scalability,\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/flume-features-limitations\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2018-02-19T05:16:55+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2021-05-09T07:38:34+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/apache-flume-features-limitations.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"802\" \/>\n\t<meta property=\"og:image:height\" content=\"420\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Apache Flume Features & Limitations of Apache Flume - 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