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Taking a look at the JVM tool

Jstat – Analysis

Ram Lakshmanan
jstat
© Shutterstock / Maxger

What are the uses of jstat and what are its limitations? It is a Java virtual machine tool for monitoring statistics and captures metrics when the JVM is running without any pre-requisite instrumentation. In this article, find out how to launch jstat, what the data it generates means, and what tool you can use to analyze this data.

Jstat is a simple utility tool, that is present in JDK to provide JVM performance-related statistics like garbage collection and compilation activities. The major strength of jstat is its ability to capture these metrics dynamically when JVM is running without any pre-requisite instrumentation.

What do we mean by that? Say for example if you want to capture garbage collection related statistics, you need to pass below arguments before you start the JVM:

-Xlog:gc*:file={file-path}

This argument will enable GC logs and print them in the specified file path. Suppose you haven’t passed this argument, then GC related statistics will not be generated. This is where jstat can come handy. Dynamically, you can connect to JVM and capture GC, compilation related statistics as shown below.

How to launch jstat

Execute the below command. It’s a simple option to launch jstat.

jstat -gc -t 11656 10000 30

-gc: Garbage collection related statistics will be printed
-t: timestamp since JVM started will be printed
11656: target JVM process Id
10000: statistics will be printed every 10,000 milliseconds (i.e. 10 seconds).
30: statistics will be printed for 30 iterations. Thus, the above option will cause the JVM to print metrics for 300 seconds (i.e. 10 seconds x 30 iterations).

(Note besides -gc, you can pass various other options to generate different data sets. For more details on different options, refer here.)

Data generated by jstat

When you launch jstat with above options, here is the output that will be generated:

jstat

Fig: jstat output

Timestamp – time since the start time of the target JVM in seconds.
S0C – Survivor 0 region capacity in KB
S1C – Survivor 1 region capacity in KB
S0U – Survivor 0 region utilized space in KB
S1U – Survivor 1 region utilized space in KB
EC – Eden region capacity in KB
EU – Eden region’s utilized space in KB
OC – Old region capacity in KB
OU – Old region’s utilized space in KB
MC – Metaspace region capacity in KB
MU – Metaspace region utilized space in KB
CCSC – Compressed Class space regions capacity in KB
CCSU – Compressed Class space regions utilized space in KB
YGC – Number of Young GC events that has occurred so far
YGCT – Amount of Young GC time spent so far
FGC – Number of Full GC events that has occurred so far
FGCT – Amount of Full GC time spent so far
GCT – total amount of GC time spent so far (basically YGCT + FGCT)

SEE ALSO: Data recovery: What matters when disaster hits

How to interpret jstat output

Equipped with this information let’s try to interpret the first line printed by the jstat tool in the above example:

jstat

Fig: jstat output’s first line

 

Timestamp Time since JVM has been started in seconds = 164.9 seconds
Young generation capacity Young Generation is made up of Eden region, Survivor 0, Survivor 1. Thus, capacity is:

S0C + S1C + EC

= 116224.0 + 116224.0 + 116736.0

= 349184 kb

= 341 mb

Young generation utilized size S0U + S1U + EU = 0 + 1520 + 68761.8

= 70281.8 kb

= 68.63 mb

Old generation capacity OC = 431616 kb

= 421.5 mb

Old generation utilized size OU = 280502.5 kb

>= 273.93 mb

Metaspace capacity MC = 32384 kb

= 31.62 mb

Metaspace utilized size M = 31155.5 kb<

= 30.42mb

Young GC Count YGC = 29
Time spent in Young GC YGCT = 0.836 seconds
Total time spent in GC GCT = 2.27 seconds

Tool to analyze jstat output

One challenge with jstat is you need to manually analyze the generated statistics. It will be tedious, as you can see just to understand/interpret one single line it takes quite a long time. You can use the GCeasy tool, which can parse jstat output and generate insightful graphs and metrics.

Here is the jstat analysis report generated by GCeasy by analyzing the above jstat output.

SEE ALSO: In Focus: Code Generation

Limitation of jstat

There are certain limitations:

It doesn’t provide rich detailed information about GC activities. It only provides just enough information. For example, from jstat you will not know:

  • If multiple GC events are reported with in one-time sample, we wouldn’t know what the pause time of each GC event was.
  • How much time is spent in Sys (i.e. kernel), user (i.e. java layer).
  • How many GC threads are working and how much time they are taking?
  • One GC event has several subphases (like initial mark, clean-up, remark, concurrent mark….). The break down of information isn’t available.
  • How many bytes are reclaimed by each GC event.

Sometimes data reported by jstat can be misleading as well.

If you would like to do accurate GC analysis, GC logs is the more reliable way.

Author
Ram Lakshmanan
Every single day, millions & millions of people in North America—bank, travel, and commerce—use the applications that Ram Lakshmanan has architected. Ram is an acclaimed speaker in major conferences on scalability, availability, and performance topics. Recently, he has founded a startup, which specializes in troubleshooting performance problems.

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