解释jstack输出
我有一个java进程使用BatchInserter将大量.csv文件中的大量数据加载到Neo4j数据库中。 我用的是：
- OpenJDK 7
- Ubuntu 12.04
- Neo4j 2.0 M3
加载第一个164 GB（根据ls -lh ）后，文件夹大小停止增加，但进程继续运行，没有释放内存，CPU仍然是100％（全部根据htop ）。
加载过程是单线程的，只有JVM使用多个线程 – 我猜是ParallelGC 。
我不确定如何诊断这类问题，但被指示尝试jstack ，所以将其输出包含在下面。
任何人都知道出了什么问题，或者对如何进行诊断提出建议？
Full thread dump OpenJDK 64-Bit Server VM (22.0-b10 mixed mode): "Attach Listener" daemon prio=10 tid=0x00007fc3a4001000 nid=0x5636 runnable [0x0000000000000000] java.lang.Thread.State: RUNNABLE "Service Thread" daemon prio=10 tid=0x00007fcf58123000 nid=0x4545 runnable [0x0000000000000000] java.lang.Thread.State: RUNNABLE "C2 CompilerThread1" daemon prio=10 tid=0x00007fcf58120800 nid=0x4544 waiting on condition [0x0000000000000000] java.lang.Thread.State: RUNNABLE "C2 CompilerThread0" daemon prio=10 tid=0x00007fcf5811d800 nid=0x4543 waiting on condition [0x0000000000000000] java.lang.Thread.State: RUNNABLE "Signal Dispatcher" daemon prio=10 tid=0x00007fcf5811b800 nid=0x4542 waiting on condition [0x0000000000000000] java.lang.Thread.State: RUNNABLE "Finalizer" daemon prio=10 tid=0x00007fcf580c4800 nid=0x4541 in Object.wait() [0x00007fc3f3cfb000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) - waiting on (a java.lang.ref.ReferenceQueue$Lock) at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:135) - locked (a java.lang.ref.ReferenceQueue$Lock) at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:151) at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:177) "Reference Handler" daemon prio=10 tid=0x00007fcf580c2000 nid=0x4540 in Object.wait() [0x00007fc3f3dfc000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) - waiting on (a java.lang.ref.Reference$Lock) at java.lang.Object.wait(Object.java:503) at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:133) - locked (a java.lang.ref.Reference$Lock) "main" prio=10 tid=0x00007fcf58007800 nid=0x452c runnable [0x00007fcf606b7000] java.lang.Thread.State: RUNNABLE at java.lang.String.substring(String.java:1960) at java.lang.String.subSequence(String.java:1993) at java.util.regex.Pattern.split(Pattern.java:1202) at com.ldbc.socialnet.neo4j.CsvFileReader.parseLine(CsvFileReader.java:73) at com.ldbc.socialnet.neo4j.CsvFileReader.nextLine(CsvFileReader.java:61) at com.ldbc.socialnet.neo4j.CsvFileReader.hasNext(CsvFileReader.java:33) at com.ldbc.socialnet.neo4j.CsvFileInserter.bufferLines(CsvFileInserter.java:62) at com.ldbc.socialnet.neo4j.CsvFileInserter.insertAllBuffered(CsvFileInserter.java:93) at com.ldbc.socialnet.neo4j.LdbcSocialNeworkNeo4jImporter.load(LdbcSocialNeworkNeo4jImporter.java:79) at com.ldbc.socialnet.neo4j.LdbcSocialNeworkNeo4jImporter.main(LdbcSocialNeworkNeo4jImporter.java:49) "VM Thread" prio=10 tid=0x00007fcf580ba000 nid=0x453f runnable "GC task thread#0 (ParallelGC)" prio=10 tid=0x00007fcf58012800 nid=0x452d runnable "GC task thread#1 (ParallelGC)" prio=10 tid=0x00007fcf58014800 nid=0x452e runnable "GC task thread#2 (ParallelGC)" prio=10 tid=0x00007fcf58016000 nid=0x452f runnable "GC task thread#3 (ParallelGC)" prio=10 tid=0x00007fcf58018000 nid=0x4530 runnable "GC task thread#4 (ParallelGC)" prio=10 tid=0x00007fcf5801a000 nid=0x4531 runnable "GC task thread#5 (ParallelGC)" prio=10 tid=0x00007fcf5801b800 nid=0x4532 runnable "GC task thread#6 (ParallelGC)" prio=10 tid=0x00007fcf5801d800 nid=0x4533 runnable "GC task thread#7 (ParallelGC)" prio=10 tid=0x00007fcf5801f800 nid=0x4534 runnable "GC task thread#8 (ParallelGC)" prio=10 tid=0x00007fcf58021000 nid=0x4535 runnable "GC task thread#9 (ParallelGC)" prio=10 tid=0x00007fcf58023000 nid=0x4536 runnable "GC task thread#10 (ParallelGC)" prio=10 tid=0x00007fcf58025000 nid=0x4537 runnable "GC task thread#11 (ParallelGC)" prio=10 tid=0x00007fcf58026800 nid=0x4538 runnable "GC task thread#12 (ParallelGC)" prio=10 tid=0x00007fcf58028800 nid=0x4539 runnable "GC task thread#13 (ParallelGC)" prio=10 tid=0x00007fcf5802a800 nid=0x453a runnable "GC task thread#14 (ParallelGC)" prio=10 tid=0x00007fcf5802c800 nid=0x453b runnable "GC task thread#15 (ParallelGC)" prio=10 tid=0x00007fcf5802e000 nid=0x453c runnable "GC task thread#16 (ParallelGC)" prio=10 tid=0x00007fcf58030000 nid=0x453d runnable "GC task thread#17 (ParallelGC)" prio=10 tid=0x00007fcf58032000 nid=0x453e runnable "VM Periodic Task Thread" prio=10 tid=0x00007fcf5812d800 nid=0x4546 waiting on condition JNI global references: 175 Heap PSYoungGen total 11211840K, used 7045440K [0x00007fcb95000000, 0x00007fcf3d160000, 0x00007fcf55000000) eden space 7045440K, 100% used [0x00007fcb95000000,0x00007fcd43050000,0x00007fcd43050000) from space 4166400K, 0% used [0x00007fce39510000,0x00007fce39510000,0x00007fcf379d0000) to space 4035328K, 0% used [0x00007fcd43050000,0x00007fcd43050000,0x00007fce39510000) PSOldGen total 31457280K, used 31300002K [0x00007fc415000000, 0x00007fcb95000000, 0x00007fcb95000000) object space 31457280K, 99% used [0x00007fc415000000,0x00007fcb8b668b98,0x00007fcb95000000) PSPermGen total 21248K, used 7487K [0x00007fc40aa00000, 0x00007fc40bec0000, 0x00007fc415000000) object space 21248K, 35% used [0x00007fc40aa00000,0x00007fc40b14ff48,0x00007fc40bec0000)
特别是，任何人都可以对这些堆值进行一些了解或建议对它们进行良好的阅读吗？
Heap PSYoungGen total 16348096K, used 12660905K [0x00007f833a560000, 0x00007f87639c0000, 0x00007f8765000000) eden space 15282432K, 82% used [0x00007f833a560000,0x00007f863f18a688,0x00007f86df1a0000) from space 1065664K, 0% used [0x00007f86df1a0000,0x00007f86df1a0000,0x00007f8720250000) to space 1036288K, 0% used [0x00007f87245c0000,0x00007f87245c0000,0x00007f87639c0000) ParOldGen total 34952576K, used 34903343K [0x00007f7ae5000000, 0x00007f833a560000, 0x00007f833a560000) object space 34952576K, 99% used [0x00007f7ae5000000,0x00007f833754bd90,0x00007f833a560000) PSPermGen total 21248K, used 7130K [0x00007f7adfe00000, 0x00007f7ae12c0000, 0x00007f7ae5000000) object space 21248K, 33% used [0x00007f7adfe00000,0x00007f7ae04f6860,0x00007f7ae12c0000)
看起来你的进程几乎没有内存：
eden space 7045440K, 100% used object space 31457280K, 99% used
在这种情况下，GC可能会连续运行，尝试释放一些内存，消耗掉所有CPU。 因此应用程序逻辑线程处于严重饥饿状态。 您可以通过-Xmx JVM选项添加更多内存或分析应用程序。 通过JVisualVM，Jprofiler或其他工具进行性能分析将为您提供重要的运行时数据：
- 内存分配动态。 如果内存消耗一直在增加，那么您可能会发生内存泄漏
- 堆内容以找出占据妈妈的内容
- GC统计数据
根据这些数据，您将能够解决问题。