Kafka Common Commands
The following is a summary of Kafka common command line:
1. View topic Details
./kafka-topics.sh-zookeeper 127.0.0.1:2181-describe-topic TestKJ1
2. Add a copy for topic
./kafka-reassign-partitions.sh-zookeeper 127.0.0.1:2181-reassignment-json-file Json/partitions-to-move.json- Execute
3. Create To
This article to share the content is about Kafka introduction and PHP-based Kafka installation and testing, the content is very detailed, the need for friends can refer to, hope can help you.
Brief introduction
Kafka is a high-throughput distributed publishing and subscription messaging system
Kafka role must be known
Background:Various Application Systems in today's society, such as business, social networking, search, and browsing, constantly produce information like information factories. In The Big Data era, we are faced with the following challenges:
How to collect this huge information
How to analyze it
How to implement the above two points in a timely manner
These challenges form a business demand model, that is, information about producer production (produce) and consumer consumption (consume) (pr
Kafka installation and use of Kafka-PHP extension, kafkakafka-php Extension
If it is used, it will be a little output, or you will forget it after a while, so here we will record the installation process of the Kafka trial and the php extension trial.
To be honest, if it is used in the queue, it is better than PHP, or Redis. It's easy to use, but Redis cannot hav
Reference Site:https://github.com/yahoo/kafka-managerFirst, the function
Managing multiple Kafka clusters
Convenient check Kafka cluster status (topics,brokers, backup distribution, partition distribution)
Select the copy you want to run
Based on the current partition status
You can choose Topic Configuration and Create topic (different c
The previous introduction of how to use thrift source production data, today describes how to use Kafka sink consumption data.In fact, in the Flume configuration file has been set up with Kafka sink consumption dataAgent1.sinks.kafkaSink.type =Org.apache.flume.sink.kafka.KafkaSinkagent1.sinks.kafkaSink.topic=TRAFFIC_LOGagent1.sinks.kafkaSink.brokerList=10.208.129.3:9092,10.208.129.4:9092,10.208.129.5:9092ag
To start the Kafka service:
bin/kafka-server-start.sh Config/server.properties
To stop the Kafka service:
bin/kafka-server-stop.sh
Create topic:
bin/kafka-topics.sh--create--zookeeper hadoop002.local:2181,hadoop001.local:2181,hadoop003.local:2181-- Replication-facto
ERROR Log event analysis in kafka broker: kafka. common. NotAssignedReplicaException,
The most critical piece of log information in this error log is as follows, and most similar error content is omitted in the middle.
[2017-12-27 18:26:09,267] ERROR [KafkaApi-2] Error when handling request Name: FetchRequest; Version: 2; CorrelationId: 44771537; ClientId: ReplicaFetcherThread-2-2; ReplicaId: 4; MaxWait: 50
1. OverviewIn the "Kafka combat-flume to Kafka" in the article to share the Kafka of the data source production, today for everyone to introduce how to real-time consumption Kafka data. This uses the real-time computed model--storm. Here are the main things to share today, as shown below:
Data consumption
First attach the Kafka operation log profile: Log4j.propertiesSet the log according to the appropriate requirements.#日志级别覆盖规则 Priority: All off#1The . Sub-log Log4j.logger overwrites the primary log Log4j.rootlogger, where the log output level is set, threshold sets the Appender log receive level;2. Log4j.logger level below Threshold,appender receive level depends on threshold level;3the Log4j.logger level above the Threshold,appender receive level de
Background:In the era of big data, we are faced with several challenges, such as business, social, search, browsing and other information factories, which are constantly producing various kinds of information in today's society:
How to collect these huge information
how to analyze how it is
done in time as above two points
The above challenges form a business demand model, which is the information of producer production (produce), consumer consumption (consume) (processing analysis), an
The MAVEN components are as follows: org.apache.spark spark-streaming-kafka-0-10_2.11 2.3.0The official website code is as follows:Pasting/** Licensed to the Apache software Foundation (ASF) under one or more* Contributor license agreements. See the NOTICE file distributed with* This work for additional information regarding copyright ownership.* The ASF licenses this file to under the Apache License, Version 2.0* (the "License"); You are no
I. Kafka INTRODUCTION
Kafka is a distributed publish-Subscribe messaging System . Originally developed by LinkedIn, it was written in the Scala language and later became part of the Apache project. Kafka is a distributed, partitioned, multi-subscriber, redundant backup of the persistent log service . It is mainly used for the processing of active streaming data
In the previous blog, how to send each record as a message to the Kafka message queue in the project storm. Here's how to consume messages from the Kafka queue in storm. Why the staging of data with Kafka Message Queuing between two topology file checksum preprocessing in a project still needs to be implemented.
The project directly uses the kafkaspout provided
Learning questions: Does 1.kafka need zookeeper?What is 2.kafka?What concepts does 3.kafka contain?4. How do I simulate a client sending and receiving a message preliminary test? (Kafka installation steps)5.kafka cluster How to interact with zookeeper? 1.
I. OverviewThe spring integration Kafka is based on the Apache Kafka and spring integration to integrate KAFKA, which facilitates development configuration.Second, the configuration1, Spring-kafka-consumer.xml 2, Spring-kafka-producer.xml 3, Send Message interface Kafkaserv
Flume and Kakfa example (KAKFA as Flume sink output to Kafka topic)To prepare the work:$sudo mkdir-p/flume/web_spooldir$sudo chmod a+w-r/flumeTo edit a flume configuration file:$ cat/home/tester/flafka/spooldir_kafka.conf# Name The components in this agentAgent1.sources = WeblogsrcAgent1.sinks = Kafka-sinkAgent1.channels = Memchannel# Configure The sourceAgent1.sources.weblogsrc.type = SpooldirAgent1.source
I. Kafka INTRODUCTIONKafka is a distributed publish-subscribe messaging system. Originally developed by LinkedIn, it was written in the Scala language and later became part of the Apache project. Kafka is a distributed, partitioned, multi-subscriber, redundant backup of the persistent log service. It is mainly used for the processing of active streaming data (real-time computing).In big Data system, often e
1. Background information
Many of the company's platforms generate a large number of logs (typically streaming data, such as the PV of search engines, queries, etc.), which require a specific log system, which in general requires the following characteristics:
(1) Construct the bridge of application system and analysis system, and decouple the correlation between them;
(2) support the near real-time on-line analysis system and the off-line analysis system similar to Hadoop;
(3) with high scalabi
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