Luca Canali on 28 Jul 2015

Topic: this post is about some simple tools and techniques that can be used to drill down high-latency I/O events using SystemTap probes.

The problem: Operations with high latency on a filesystem and/or a storage volume can sometimes be attributed to just a few disks 'misbehaving', possibly because they are suffering mechanical failures and/or are going to break completely in the near future.

I/Os of high latency on just a few disks can then appear as latency outliers when accessing volumes build on a large number of disks and overall affect the performance of the entire storage. I write this having in mind the example of a storage system built with (SATA) JBODs using Oracle ASM as volume manager/DB filesystem. However the main ideas and tools described in this post apply to many other volume managers and file systems, including HDFS.

The standard tools: One way to find that one or more disks are serving I/O requests with high latency is with the use of standard Linux tools such as iostatsar orcollectl. Typically you would use those tools to spot anomalous values of average service time, average wait time and also of queue size.

A structured approach on how to do this is described in Brendan Gregg(link is external)'s USE method(link is external) and thetools that can be used in Linux(link is external) to implement it.

SystemTap scripts: In this post we focus on a technique and a couple of simple scripts that can be used to identify disks serving I/O with high latency using SystemTap(link is external) probes to investigate I/O latency of the block devices.

The script blockio_latency_outliers_per_device.stp(link is external) provides a measurement of some basics latency statistics for block device, including number of I/Os, average andmaximum latency. The script also provides details of all the I/O where the latency is above a certain programmable threshold (the default threshold is set at 500 microseconds).

An example of its use (edited output for clarity) is here below. Note the latency warning message and overall the very large maximum value measured for the latency of the /dev/sdy block device:

[root@myhost(link sends e-mail)] # stap -v blockio_latency_outliers_per_device.stp 10

Measuring block I/O latency and statistics

A warning will be printed for I/Os with latency higher than 500000 microseconds

Statistics will be printed every 10 seconds. Press CTRL-C to stop

...

latency warning, >500000 microsec: device=sdy, sector=166891231, latency=714984

latency warning, >500000 microsec: device=sdy, sector=165679327, latency=582708

latency warning, >500000 microsec: device=sdy, sector=167102975, latency=1162550

....

I/O latency basic statistics per device, measurement time: 10 seconds

Latency measured in microseconds

Disk name          Num I/Os    Min latency    Avg latency    Max latency

....

sdu                     219            106           6217          27117

sdz                     200            123           5995          27205

sdq                     211             71           6553          31120

sdh                     256            103           6643          22663

sds                     224            101           6610          29743

sdm                     238             92           7550          35571

sde                     243             90           8652          52029

sdt                     200            105           5997          25180

sdk                     200             94           5696          35057

sdi                     206             99           7849          30636

sdg                     269             74           6746          36746

sdy                     197            102          98298        1167977

sdr                     200             89           6559          27873

sdl                     200            140           8789          31996

sdw                     210             99           7009          37118

sdd                     217             94           7440          56071

sdn                     205             99           6628          41339

....

When candidate disks for high latency have been identified, the second step is to further drill down using the script blockio_rq_issue_filter_latencyhistogram.stp(link is external). This script gathers and displays I/O latency histograms for a subset of block devices that can be specified using filters in the script header. The default filters are:

# SystemTap variables used to define filters, edit as needed

global IO_size = 8192    # this will be used as a filter for the I/O request size

# the value 8192 targets 8KB operations for Oracle

# single-block I/O

# use the value -1 to disable this filter

global IO_operation = 0  # this will be used as a filter: only read operations

# a value of 0 considers only read operations

# (1 is for write), use -1 to disable this filter

global IO_devmaj = -1    # this will be used as a filter:

# device major number (-1 means no filter)

# ex: use the value 253 for device mapper block devices

global IO_devmin = -1    # device minor number (or -1 if no filter)

You can use  blockio_rq_issue_filter_latencyhistogram.stp(link is external) to drill down on the latency histogram for those disks that have shown high latency I/O and also compare them with "good" disks. In the example above the candidate "trouble disk" is /dev/sdy with major number 65 and minor 128 (you can major and minor device numbers for "sdy" simply using ls -l /dev/sdy).

Example:

stap -v blockio_rq_issue_filter_latencyhistogram.stp 10

Block I/O latency histograms from kernel trace points

Filters:

    IO_size = 8192

    IO_operation = 0 (0=read, 1=write, -1=disable filter)

    IO_devmaj = 65 (-1=disable filter)

    IO_devmin = 128 (-1=disable filter)

lock I/O latency histogram, measurement time: 10 seconds, I/O count: 199

Value = latency bucket (microseconds), count=I/O operations in 10 seconds

value |-------------------------------------------------- count

16 |                                                    0

32 |                                                    0

64 |@                                                   2

128 |@@@@@@@                                            14

256 |@@                                                  4

512 |@                                                   2

1024 |@@@                                                 7

2048 |@@@@@@@@@                                          19

4096 |@@@@@@@@@@@@@@@@@@                                 37

8192 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@                      59

16384 |@@@@@@@                                            14

32768 |                                                    0

65536 |@@@@@          HIGH                                10

131072 |@@@@@          LATENCY                             11

262144 |@@@@@          I/O                                 10

524288 |@@@            OPERATIONS                           6

1048576 |@@                                                  4

2097152 |                                                    0

 

Note the presence of several I/O operations at high latency together with more normal I/O latecy, for example I/Os served from SATA disks at around 8 ms and also I/O served from the controller cache at sub-millisecond latency.

For comparison here below is the latency histogram measured on another disk while the same workload was running. We can see that in this case high latency points found in the previous example are no more present. Most of the I/O operations are around 8 ms latency and some operations served from cache at sub-millisecond latency. The I/O reported for the /dev/sdy disks with latency of 64 ms and above are not present in this case.

stap -v blockio_rq_issue_filter_latencyhistogram.stp 10

Block I/O latency histograms from kernel trace points

Filters:

IO_size = 8192

IO_operation = 0 (0=read, 1=write, -1=disable filter)

IO_devmaj = 65 (-1=disable filter)

IO_devmin = 48 (-1=disable filter)

Block I/O latency histogram, measurement time: 10 seconds, I/O count: 196

Value = latency bucket (microseconds), count=I/O operations in 10 seconds

value |-------------------------------------------------- count

32 |                                                    0

64 |                                                    0

128 |@@@@@@@@@                                          19

256 |@@@@@@@@                                           16

512 |                                                    1

1024 |@@@@                                                9

2048 |@@@@@@@@@@@@@@                                     28

4096 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@                       56

8192 |@@@@@@@@@@@@@@@@@@@@@@@@                           49

16384 |@@@@@@@@@                                          18

32768 |                                                    0

65536 |                                                    0

The tests reported here have been performed on a old system running RHEL 5 (kernel 2.6.18-371)  and SystemTap v. 1.8, however the scripts have also been tested on OL and CentOS 7.1 (kernel 3.10.0-229) and SystemTap 2.8. If you are using SystemTap 2.6 or above you can use the scripts blockio_rq_issue_latencyhistogram_new.stp(link is external)and blockio_rq_issue_filter_latencyhistogram_new.stp(link is external) instead.

Conclusion: In this post we have shown a simple technique to troubleshoot I/O latency outliers and in particular on how to drill down on I/Os served at high latency because of one or more misbehaving disk in the storage volume/filesystem. The investigation has been done using SystemTap scripts used first to discover which disks were serving some of their I/O s with high latency and then drilling down on specific devices with the use of latency histograms. The fact of identifying and later replacing the badly performing disks can be beneficial for the performance of the entire storage systems.

Download: The tools discussed in this post can be downloaded from this webpage and from Github(link is external).

Acknowledgements and additional links: Brendan Gregg(link is external) has published an extensive set of articles and tools on performance tuning, including storage latency investigations.

For more information and examples on how to use SystemTap see the SystemTap wiki(link is external)

Additional tools for Oracle ASM I/O investigations also see Bertrand Drouvot's asm_metrics.pl(link is external)

Kevin Closson's SLOB(link is external) was used as workload generator for the examples discussed here.

Additional links on tools and techniques on Oracle I/O troubleshooting in this blog: Heat Map Visualization of I/O Latency with SystemTap and PyLatencyMap(link is external)Event Histogram Metric and Oracle 12c(link is external) and Life of an Oracle I/O: Tracing Logical and Physical I/O with Systemtap(link is external)

Diagnose High-Latency I/O Operations Using SystemTap的更多相关文章

  1. SystemTap Beginners Guide

    SystemTap 3.0 SystemTap Beginners Guide Introduction to SystemTap Edition 3.0   Red Hat, Inc. Don Do ...

  2. Examining Huge Pages or Transparent Huge Pages performance

    Posted by William Cohen on March 10, 2014 All modern processors use page-based mechanisms to transla ...

  3. HazelCast 的内存管理原理

    As it is said in the recent article "Google: Taming the Long Latency Tail - When More Machines ...

  4. Windows常用性能计数器总结

    基础监控: Processor:% Processor Time CPU当前利用率,百分比 Memory:Available MBytes 当前可用内存,兆字节(虚拟内存不需要监控,只有当物理内存不够 ...

  5. 【RabbitMQ】 RabbitMQ安装

    MQ全称为Message Queue, 消息队列(MQ)是一种应用程序对应用程序的通信方法.应用程序通过读写出入队列的消息(针对应用程序的数据)来通信,而无需专用连接来链接它们.消息传递指的是程序之间 ...

  6. Extension of write anywhere file system layout

    A file system layout apportions an underlying physical volume into one or more virtual volumes (vvol ...

  7. Spark第一周

    Why Scala 在数据集不是很大的时候,开发人员可以使用python.R.MATLAB等语言在单机上处理数据集.但是在大数据时代,数据集少说都是TB.PB级别,此时便需要分布式地处理.相较于上述语 ...

  8. Linux安装RabbitMQ教程(文件下载地址+安装命令+ 端口开放 + 用户创建 +配置文件模板+端口修改)

    前言 1.安装RabbitMQ前需先安装erlang, 且两者需要版本对应, 否则无法正常启动RabbitMQ (本教程使用22.0.7版本的erlang和3.8.6版本的Rabbitmq) 版本对应 ...

  9. 用systemtap对sysbench IO测试结果的分析1

    http://www.actionsky.com/docs/archives/171  2016年5月6日  黄炎 近期在一些简单的sysbench IO测试中, 遇到了一些不合常识的测试结果. 从结 ...

随机推荐

  1. C# 传值和传引用 ( ref out in )

    引用类型的变量不直接包含其数据:它包含的是对其数据的引用.当通过值传递引用类型的参数时,有可能更改引用所指向的数据,如某类成员的值(更改属性的值),但是无法更改引用本身的值:也就是说,不能使用相同的引 ...

  2. 在Azure Ubunt Server 14.04虚机中使用Deep-Visualization-Toolbox

      参考网站 a)   https://zhuanlan.zhihu.com/p/24833574?utm_source=tuicool&utm_medium=referral b)   ht ...

  3. SqlServer知识点-操作xml

    一.开发环境 SQL2010 二.开发过程 1.声明一个xml类型变量 DECLARE @xmlInfo XML; SET @xmlInfo = '<CompanyGroup> <C ...

  4. 逻辑回归(Logistic Regression)推导

    出自BYRans博客:http://www.cnblogs.com/BYRans/ 本文主要讲解分类问题中的逻辑回归.逻辑回归是一个二分类问题. 二分类问题 二分类问题是指预测的y值只有两个取值(0或 ...

  5. Java线程及Jvm监控工具

    Java线程状态 线程的五种状态 * 新建:new(时间很短) * 运行:runnable * 等待:waitting(无限期等待),timed waitting(限期等待) * 阻塞:blocked ...

  6. UVM基础之---------uvm report 机制分析

    uvm 中的信息报告机制相对来说比较简单,功能上来说主要分为两部分: 第一通过ID对component的信息报告冗余级别进行控制,针对每个冗余级别进行不同的行为控制.这部分工作主要由uvm_repor ...

  7. Java中PrintStream(打印输出流)

    Java中PrintStream(打印输出流)   PrintStream 是打印输出流,它继承于FilterOutputStream. PrintStream 是用来装饰其它输出流.它能为其他输出流 ...

  8. MFC_1.1 基本知识

    如何创建一个MFC项目 选择 MFC 应用程序进行创建,不要使用非英文名 选择对话框风格进行编写 可以通过自定义的设置修改类名 MFC 的基本知识 MFC 是纯面向对象的编程,是 SDK 经过 C++ ...

  9. RocketMQ学习笔记(14)----RocketMQ的去重策略

    1. Exactly Only Once (1). 发送消息阶段,不允许发送重复的消息 (2). 消费消息阶段,不允许消费重复的消息. 只有以上两个条件都满足情况下,才能认为消息是“Exactly O ...

  10. MySQLWorkBench怎么设置主键自增长

    参考 https://blog.csdn.net/qq_40472613/article/details/87858099 勾选AI选项,相当于执行了这个语句: AUTO_INCREMENT表示自增 ...