[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Kai Zheng updated MAPREDUCE-6729:
-
Assignee: mingleizhang (was: mingleizhang)
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Assignee: mingleizhang
>Priority: Minor
> Labels: performance, test
> Attachments: MR-6729.txt
>
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time
> consumption because of fs.delete(*,*) by the writeTest method
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Kai Zheng updated MAPREDUCE-6729:
-
Assignee: mingleizhang
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Assignee: mingleizhang
>Priority: Minor
> Labels: performance, test
> Attachments: MR-6729.txt
>
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time
> consumption because of fs.delete(*,*) by the writeTest method
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Attachment: MR-6729.txt
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
> Attachments: MR-6729.txt
>
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time
> consumption because of fs.delete(*,*) by the writeTest method
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time consumption
because of fs.delete(*,*) by the writeTest method
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time consumption
because of fs.delete(*,*)
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time
> consumption because of fs.delete(*,*) by the writeTest method
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. We need to replace or improve
this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs);
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time consumption
because of fs.delete(*,*)
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time consumption
because of fs.delete(*,*)
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time
> consumption because of fs.delete(*,*)
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time consumption
because of fs.delete(*,*)
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time because of
fs.delete(*,*)
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time
> consumption because of fs.delete(*,*)
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs); // this line of code will cause extra time because of
fs.delete(*,*)
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. So we need to replace or
improve this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. So we need to replace
> or improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs); // this line of code will cause extra time because
> of fs.delete(*,*)
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput while the files are lots of. We need to replace or improve
this hack to prevent this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as a distributed i/o benchmark tool. Then especially
writes plenty of files to disk or read from, both can cause performance issue
and imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput for us. We need to replace or improve this hack to prevent
this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as a distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput while the files are lots of. We need to replace or
> improve this hack to prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs);
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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[jira] [Updated] (MAPREDUCE-6729) Hitting performance and error when lots of files to write or read
[
https://issues.apache.org/jira/browse/MAPREDUCE-6729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
mingleizhang updated MAPREDUCE-6729:
Description:
When doing DFSIO test as distributed i/o benchmark tool. Then especially writes
plenty of files to disk or read from, both can cause performance issue and
imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause extra time
consumption and furthermore cause performance issue, statistical time error and
imprecise throughput for us. We need to replace or improve this hack to prevent
this from happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
was:
When doing DFSIO test as distributed i/o benchmark tool. Then especially writes
plenty of files to disk or read from, both can cause performance issue and
imprecise value in a way. The question is that existing practices needs to
delete files when before running a job and that will cause time consumption and
furthermore cause performance issue, statistical time error and imprecise
throughput for us. We need to replace or improve this hack to prevent this from
happening in the future.
{code}
public static void testWrite() throws Exception {
FileSystem fs = cluster.getFileSystem();
long tStart = System.currentTimeMillis();
bench.writeTest(fs);
long execTime = System.currentTimeMillis() - tStart;
bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
}
private void writeTest(FileSystem fs) throws IOException {
Path writeDir = getWriteDir(config);
fs.delete(getDataDir(config), true);
fs.delete(writeDir, true);
runIOTest(WriteMapper.class, writeDir);
}
{code}
[https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
> Hitting performance and error when lots of files to write or read
> -
>
> Key: MAPREDUCE-6729
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6729
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: benchmarks, performance, test
>Reporter: mingleizhang
>Priority: Minor
> Labels: performance, test
>
> When doing DFSIO test as distributed i/o benchmark tool. Then especially
> writes plenty of files to disk or read from, both can cause performance issue
> and imprecise value in a way. The question is that existing practices needs
> to delete files when before running a job and that will cause extra time
> consumption and furthermore cause performance issue, statistical time error
> and imprecise throughput for us. We need to replace or improve this hack to
> prevent this from happening in the future.
> {code}
> public static void testWrite() throws Exception {
> FileSystem fs = cluster.getFileSystem();
> long tStart = System.currentTimeMillis();
> bench.writeTest(fs);
> long execTime = System.currentTimeMillis() - tStart;
> bench.analyzeResult(fs, TestType.TEST_TYPE_WRITE, execTime);
> }
> private void writeTest(FileSystem fs) throws IOException {
> Path writeDir = getWriteDir(config);
> fs.delete(getDataDir(config), true);
> fs.delete(writeDir, true);
> runIOTest(WriteMapper.class, writeDir);
> }
> {code}
> [https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-jobclient/src/test/java/org/apache/hadoop/fs/TestDFSIO.java]
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