Apache
/
hadoop
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

HADOOP-14019. Fix some typos in the s3a docs. Contributed by Steve Loughran 

(cherry picked from commit bdad8b7b97)
This commit is contained in:
Mingliang Liu 2017-02-16 16:41:31 -08:00
parent 83a5896180
commit 3b4f840ccb
1 changed files with 13 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
hadoop-tools/hadoop-aws/src/site/markdown/tools/hadoop-aws/index.md
View File

@ -989,7 +989,7 @@ This is because the property values are kept in these files, and cannot be
dynamically patched.
Instead, callers need to create different configuration files for each
bucket, setting the base secrets (`fs.s3a.bucket.nightly.access.key`, etc),
bucket, setting the base secrets (`fs.s3a.access.key`, etc),
then declare the path to the appropriate credential file in
a bucket-specific version of the property `fs.s3a.security.credential.provider.path`.
@ -1063,7 +1063,7 @@ declaration. For example:
### <a name="s3a_fast_upload"></a>Stabilizing: S3A Fast Upload
**New in Hadoop 2.7; significantly enhanced in Hadoop 2.9**
**New in Hadoop 2.7; significantly enhanced in Hadoop 2.8**
Because of the nature of the S3 object store, data written to an S3A `OutputStream`
@ -1223,8 +1223,18 @@ consumed, and so eliminates heap size as the limiting factor in queued uploads
<value>disk</value>
</property>
<property>
<name>fs.s3a.buffer.dir</name>
<value></value>
<description>Comma separated list of temporary directories use for
storing blocks of data prior to their being uploaded to S3.
When unset, the Hadoop temporary directory hadoop.tmp.dir is used</description>
</property>
```
This is the default buffer mechanism. The amount of data which can
be buffered is limited by the amount of available disk space.
#### <a name="s3a_fast_upload_bytebuffer"></a>Fast Upload with ByteBuffers: `fs.s3a.fast.upload.buffer=bytebuffer`
@ -1238,7 +1248,7 @@ The amount of data which can be buffered is
limited by the Java runtime, the operating system, and, for YARN applications,
the amount of memory requested for each container.
The slower the write bandwidth to S3, the greater the risk of running out
The slower the upload bandwidth to S3, the greater the risk of running out
of memory —and so the more care is needed in
[tuning the upload settings](#s3a_fast_upload_thread_tuning).