Kafka Brokers per Server Recommend 1 Kafka broker per server- Kafka not only disk-intensive but can be network intensive so if you run multiple broker in a single host network I/O can be the bottleneck . Running single broker per host and having a cl…
1.前言:一直以来SQL调优都是DBA比较费力的技术活,而且很多DBA如果没有从事过开发的工作,那么调优更是一项头疼的工作,即使是SQL调优很厉害的高手,在SQL调优的过程中也要不停的分析执行计划.加HINT.分析统计信息等等.从ORACLE 10G开始,数据库采取了很多智能化的管理工作,其中SQL优化器(SQL Tuning Advisor:STA),大大的提高了DBA进行SQL优化的效率: 2.原理介绍: When SQL statements are executed by the Ora…
测试环境 apache-jmeter-2.13 1. 问题描述 单台机器的下JMeter启动较大线程数时可能会出现运行报错的情况,或者在运行一段时间后,JMeter每秒生成的请求数会逐步下降,直到为0,即JMeter运行变得很“卡”. 2. 解决方法 1)设置JVM内存 找到JMeter bin目录下的jmeter.bat文件,notepad等文本工具打开,编辑 找到如下内容, rem See the unix startup file for the rationale of th…
说的太经典了,不敢翻译.直接上原文. 来源于: Network Protocols and Real Application Clusters (文档 ID 278132.1) PURPOSE ------- Purpose of this document is to give DBAs and Systems Administrators interested in Real Application Clusters an overview and a comparison of netwo…
场景 单台机器的下JMeter启动较大线程数时可能会出现运行报错的情况,或者在运行一段时间后,JMeter每秒生成的请求数会逐步下降,直到为0,即JMeter运行变得很"卡",这时候我们可以调整JVM内存,来对Jmeter进行优化 设置JVM内存 ①找到JMeter bin目录下的jmeter.bat文件:Linux找jmeter.sh文件,编辑打开 ②查找以下内容 rem See the unix startup file for the rationale of the follo…
This is intended to be an easy to understand FAQ on the topic of Kafka. One part is for beginners, one for advanced users and use cases. We hope you find it fruitful. If you are missing a question, please send it to your favorite Cloudera representat…
今天查看Kafka 0.10.0的官方文档,发现了这样一句话:Configuration parameter replica.lag.max.messages was removed. Partition leaders will no longer consider the number of lagging messages when deciding which replicas are in sync. 即replica.lag.max.messages参数被正式地移除了,现在topic…
DB tuning advisor是创建优化任务,对某些sql数据库进行分析,并尽量给出优化建议的一个强大的数据库工具. 自己平时几乎没用过这玩意,所以来测一测用法,其实对于一些sql一筹莫展的时候跑跑这个,看看数据库的建议也是一个突破点. 一般利用database tuning advisor的顺序: 找出要去优化调整的sql_id,创建优化任务 Login as SYSTEM (or any other user) at sqlplus and create the tuning task:…
In this post I'm going to help you understand how Kafka stores its data. I've found understanding this useful when tuning Kafka's performance and for context on what each broker configuration actually does. I was inspired by Kafka's simplicity and us…
[This article was originally written by Yves Trudeau.] http://java.dzone.com/articles/exploring-message-brokers Message brokers are not regularly covered here but are, nonetheless, important web-related technologies. Some time ago, I was asked by one…
Explore the configuration changes that Cigna’s Big Data Analytics team has made to optimize the performance of its real-time architecture. Real-time stream processing with Apache Kafka as a backbone provides many benefits. For example, this architect…
Apache Kafka is optimized for small messages. According to benchmarks, the best performance occurs with 1 KB messages. Larger messages (for example, 10 MB to 100 MB) can decrease throughput and significantly impact operations. This topic describes op…
I wrote a blog post about how LinkedIn uses Apache Kafka as a central publish-subscribe log for integrating data between applications, stream processing, and Hadoop data ingestion. To actually make this work, though, this "universal log" has to…
The new integration between Flume and Kafka offers sub-second-latency event processing without the need for dedicated infrastructure. In this previous post you learned some Apache Kafka basics and explored a scenario for using Kafka in an online appl…
When we are talking about performance of Kafka Producer, we are really talking about two different things: latency: how much time passes from the time KafkaProducer.send() was called until the message shows up in a Kafka broker. throughput: how many…
With MySQL, common configuration mistakes can cause serious performance problems. In fact, if you mis-configure just one of the many config parameters, it can cripple performance! (see examples) Of course, the performance of MySQL is often tied great…