flume kafka

SummaryThis paper mainly introduces how to use Kafka's own performance test script and Kafka Manager to test Kafka performance, and how to use Kafka Manager to monitor Kafka's working status, and finally gives the Kafka performance test report.Performance testing and cluster monitoring toolsKafka provides a number of u

I. Introduction of FlumeFlume is a distributed, reliable, and highly available mass-log aggregation system that enables the customization of various data senders in the system for data collection, while Flume provides the ability to simply process the data and write to various data-receiving parties (customizable).Design objectives:(1) ReliabilityWhen a node fails, the log can be transmitted to other nodes without loss.

IconAs shown in the Red box section, I do stability testing, when the flume run a few days later, I found that the counter value gradually become larger, to a certain value, and then become smaller, there is a cycle of the process, and therefore the desire to produce research, the following to see:if (Txneventcount = = 0) { sinkcounter.incrementbatchemptycount (); } else if (Txneventcount = = batchsize) { Sinkcounter.incrementbatchc

internal selection of a valid sink for processingThe exception section, we found that triggered the informsinkfailed () method, let's take a look at the methodpublic void Informfailure (T failedobject) {//if There are no Backoff this method is a no-op. if (!shouldbackoff) {return; } failurestate state = Statemap.get (Failedobject); Long now = System.currenttimemillis (); Long delta = now-state.lastfail; /* * When do we increase the Backoff period? * We Basically calculate the ti

Multiplexing technology is intended to send an event to a specific channel based on configuration information.A source instance can specify multiple channels, but a sink instance can only specify one channel.Flume supports fanning out the flow from one source to multiple channels. There is modes of fan out, replicating and multiplexingFlume supports two modes of output from source to multiple channel: copy and Reuse1. In copy mode, the event data received by source is output to all channel confi

Basic concepts of flume, data stream model, and flume data stream1. Basic concepts of flume AllFlumeAll related terms are in italic English. The meanings of these terms are as follows. FlumeA reliable and distributed system for collecting, aggregating, and transmitting massive log data. Web ServerOne generationEvents. Agent flumeA node in the system contains thre

Kafka in versions prior to 0.8, the high availablity mechanism was not provided, and once one or more broker outages, all partition on the outage were unable to continue serving. If the broker can never recover, or a disk fails, the data on it will be lost. One of Kafka's design goals is to provide data persistence, and for distributed systems, especially when the cluster scale rises to a certain extent, the likelihood of one or more machines going do

Flume compared with Logstash, the personal experience is as follows: Logstash more emphasis on the preprocessing of the field, while flume emphasis on data transmission; Logstash has dozens of plug-ins, flexible configuration, Flume is to emphasize the user's custom development (source and sink kind also has ten or twenty, the channel is relatively s

(logaggregation). Log aggregation typically collects log files from the server and then places them in a centralized location (file server or HDFS) for processing. However, Kafka ignores the details of the file and abstracts it more clearly into the message flow of a log or event. This makes the Kafka processing process less latency and easier to support multiple data sources and distributed data processin

In a complete large data processing system, in addition to the core of the Hdfs+mapreduce+hive composition Analysis system, data acquisition, result data export, task scheduling and other indispensable auxiliary systems are needed, and these auxiliary tools are There is a convenient open source framework in the Hadoop ecosystem. Log capture framework FlumeFlume is a distributed, reliable, and highly available system for collecting, aggregating, and transmitting large volumes of logs.

This article is forwarded from Jason's Blog, the original link Http://www.jasongj.com/2015/12/31/KafkaColumn5_kafka_benchmarkSummaryThis paper mainly introduces how to use Kafka's own performance test script and Kafka Manager to test Kafka performance, and how to use Kafka Manager to monitor Kafka's working status, and finally gives the

cache the data to be processed, Kafka has better throughput, built-in sharding, replication, fault tolerance mechanism, is a better solution for large-scale data message processing.2, website activity tracking: Site visits, search volume, or other user activity behavior such as registration, recharge, payment, purchase and other behavior can be published to the center of the topic, each type can be as a topic, these information flow can be the consum

operation records and other information sent to the Kafka, according to the actual business needs, can be real-time monitoring, or do off-line processing. Finally, one is the log collection, similar to the flume suite such as the Log collection system, but the Kafka design architecture is push/pull, suitable for heterogeneous clusters,

good performance where multiple disks is not available for checkpoint and data Directori Es.It is natural that the channel data is synchronized to disk and performance degrades, but the checkpoint mechanism is added to prevent data loss.For the deformed memory channel, which is the memory channel and the file channel used together, we do not explain here, because this mixed use, the official also give hints-not recommended in the production environment to use.The reason for this is that data lo

a certain range, it will flushprivate void Flusheventbatch (listFlush is the event in the EventList that is now being saved and emptied1. Put the event into the configured channelFor (event event:events) { listHere is the detailed procedure for putting the event into the channel, but here you notice that there are two selector getchannel methods, because there are two types of channel selector modes: Multiplexing and Replication if (restart) { logger.info ("Restarting in {}ms, ex

partition the message flow by one of the key values in the message and send the different partitions to their respective proxies. e)Pushand pull which way good L Two ways of explainingPull method: Let the user from the agent to pull the data down. Push mode: Let the agent push (push) the data to the user. L Two ways of comparisonPull mode is more commonly used, more suitable for the user's processing speed is slightly behind the situation, but also allows users to be able to catch up before the

Kafka Connector and Debezium 1. Introduce Kafka Connector is a connector that connects Kafka clusters and other databases, clusters, and other systems. Kafka Connector can be connected to a variety of system types and Kafka, the main tasks include reading from

whereabouts, we can the Enterprise Portal, the user's operation records and other information sent to the Kafka, according to the actual business needs, can be real-time monitoring, or do offline processing. Finally, one is log collection, similar to the Flume suite, such as the log collection system, but the Kafka design architecture uses push/pull, suitable fo

Kafka cluster configuration is relatively simple. For better understanding, the following three configurations are introduced here. Single Node: A broker Cluster Single Node: cluster of multiple Brokers Multi-node: Multi-broker Cluster 1. Single-node single-broker instance Configuration 1. first, start the zookeeper service Kafka. It provides the script for starting zookeeper (in the

them are framework-based Development. You can fill in your own configuration, startup, shutdown, and business logic for the specified method, I will have the opportunity to write an article to introduce it in the future; 2. For custom components, please trust GitHub. There are a lot of custom components that can be used directly ....; 9. Flume-ng cluster network topology solution: 1. Deploy a flume