Label: Flume The demo is not saying. You can search by yourself.But now the internet is mainly Flume 1.4 version number of information. Flume 1.5 In a sensational big change. Assuming you're ready to try, I'm here to introduce you to the program minimization structure, and the data that uses Mongosink is stored in MongoDB. Completely independent of execution, wit
Recently, in the Test Flume combines Kafka with spark streaming experiments. Today, the simple combination of flume and spark to make a record here, to avoid users detours. There are not thoughtful places also want to pass by the great God a lot of advice.The experiment is relatively simple, divided into two parts: first, Use avro-client send data two, Use Netcat Send Datafirst the Spark program requires Tw
Welcome to the big Data and AI technical articles released by the public number: Qing Research Academy, where you can learn the night white (author's pen name) carefully organized notes, let us make a little progress every day, so that excellent become a habit!First, the introduction of flume:Developed by Cloudera, Flume is a system that provides high availability, high reliability, distributed mass log acquisition, aggregation and transmission,
Flume: Used to collect logs and transfer logs to KAKFAKafka: As a cache, store logs from FlumeES: As a storage medium, store logsLogstash: True filtering of logsFlume deploymentGet the installation package, unzip1 wget http://10.80.7.177/install_package/apache-flume-1.7.0-bin.tar.gz tar ZXF apache-flume-1.7.0-bin.tar.gz-c/usr/local/Modify the flumen-env.sh scri
first part single node flume configuration
Installation Reference http://flume.apache.org/FlumeUserGuide.html
http://my.oschina.net/leejun2005/blog/288136
Here is a simple introduction, the command to run the agent
$ bin/flume-ng agent-n $agent _name-c conf-f conf/flume-conf.properties.template
1. The single node configuration is as follows
# example.conf:a S
Apache Next version (1.6) will bring a new component Kafkachannel, as the name implies is to use Kafka as the channel, of course, in the CDH5.3 version already exists this channel.As you know, there are three main channel commonly used:1, Memory channel: With the channel, the advantage is the fastest, easy to configure; The disadvantage is that the reliability is the worst, because once the flume process hangs the memory of the data is not out;2, File
Big Data We all know about Hadoop, but not all of Hadoop. How do we build a large database project. For offline processing, Hadoop is still more appropriate, but for real-time and relatively strong, data volume is relatively large, we can use storm, then storm and what technology collocation, in order to do a suitable for their own projects.1. What are the characteristics of a good project architecture?2. How does the project structure ensure the accuracy of the data?3. What is Kafka?How does 4.
In the flume-based log collection system (a) architecture and design, we detail the architecture design of the flume-based log collection system and why it is designed. In this section, we will describe the problems encountered in the actual deployment and use process, the functional improvements to flume, and the optimizations that are made to the system.1 Summa
Netstat-ntpl[root@bigdatahadoop sbin]#./nginx-t-c/usr/tengine-2.1.0/conf/nginx.conf
Nginx: [Emerg] "upstream" directive is isn't allowed here in/usr/tengine-2.1.0/conf/nginx.conf:47
Configuration file/usr/tengine-2.1.0/conf/nginx.conf test Failed
One more}.
16/06/26 14:06:01 WARN node. Abstractconfigurationprovider:no configuration found for this host:clin1
Java environment variable "This may not be wrong"
Org.apache.commons.cli.ParseException:The specified configuration file does not exist
Flume supports the configuration of agents through zookeeper, but this is an experimental feature. The configuration file must be uploaded to the zookeeper first. The following agent is in the structure of the Zookeeper node tree:
-/flume
|-/a1 [agent configuration file]
| |/a2 [agent profile]
classes that process the configuration file:
Org.apache.flume.node.PollingZooKeeperConfigurationProvider: If
a single-node flume deployment1 Hadoop PreparationCreate the Flume directory in HDFs and assign permissions for the flume directory to flume usersHDFs Dfs-mkdir FlumeHDFs Dfs-chown-r Flume:flume/flume2 flume-env.shEnter ${flume_home}/conf
CP
There are two ways, one is sparkstreaming in the driver from listening, flume to push the data, the other is sparkstreaming according to the time policy rotation to flume pull data.At first I thought there was only the first method, but the Nima problem is that driver up the knot is flaky, so every time I restart streaming found that every time to change the flume
Flume is a highly available, highly reliable, distributed mass log capture, aggregation, and transmission system provided by Cloudera, Flume supports the customization of various data senders in the log system for data collection, while Flume provides simple processing of data The ability to write to various data-receiving parties (customizable). The current
1) hostname error:
2011-11-14 11:44:55,497 ERROR com.cloudera.util.NetUtils: Unable to get canonical host name! test: test java.net.UnknownHostException: test: test at java.net.InetAddress.getLocalHost(InetAddress.java:1354) at com.cloudera.util.NetUtils.
Error cause: IP address cannot be obtained from hostname
Solution: add the host name to IP address ing in the/etc/hosts file.
2) Java does not follow
line 234: exec: java: not found
Error cause: the Java command does not exist.
In the distributed system, each machine has the local log that the program runs, sometimes in order to analyze the demand, have to these scattered log summary requirements, I believe many people will choose RSYNC,SCP, but they are not strong in real-time, but also bring the problem of name conflict. The scalability is not satisfactory, not elegant at all.In reality, we are confronted with the need to summarize the Nginx logs of multiple servers on the line in real time.
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.
Download apache-flume-1.7.0-bin.tar.gz, withTar -zxvfUnzip, add the settings in the/etc/profile file:Export Flume_home=/opt/apache-flume-1.7.0-binexport path= $PATH: $FLUME _home/binModify the two files under $flume_home/conf/and increase the java_home in flume-env.sh:java_home=/opt/jdk1.8.0_121Most importantly, modify
{ //no event, that is Backoffresult =Status.backoff; } //Commit a transactionTransaction.commit (); } Catch(Exception ex) {//rolling back a transactionTransaction.rollback (); Throw NewEventdeliveryexception ("Failed to log event:" +event, ex); } finally { //Close TransactionTransaction.close (); } returnresult; } } 3. Pack and place in/soft/flume/Lib under4, using the custom s
1. Background introduction Many of the company's platforms generate a large number of logs per day (typically streaming data, for example, the search engine PV, query, etc.), the processing of these logs requires a specific log system, in general, these systems need to have the following characteristics: (1) The construction of application systems and analysis systems of the bridge, and the correlation between them decoupling (2) support for near real-time online analysis system and off-line ana
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
The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion;
products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the
content of the page makes you feel confusing, please write us an email, we will handle the problem
within 5 days after receiving your email.
If you find any instances of plagiarism from the community, please send an email to:
info-contact@alibabacloud.com
and provide relevant evidence. A staff member will contact you within 5 working days.