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@@ -999,7 +999,7 @@ This is because the property values are kept in these files, and cannot be
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dynamically patched.
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Instead, callers need to create different configuration files for each
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-bucket, setting the base secrets (`fs.s3a.bucket.nightly.access.key`, etc),
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+bucket, setting the base secrets (`fs.s3a.access.key`, etc),
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then declare the path to the appropriate credential file in
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a bucket-specific version of the property `fs.s3a.security.credential.provider.path`.
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@@ -1073,7 +1073,7 @@ declaration. For example:
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### <a name="s3a_fast_upload"></a>Stabilizing: S3A Fast Upload
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-**New in Hadoop 2.7; significantly enhanced in Hadoop 2.9**
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+**New in Hadoop 2.7; significantly enhanced in Hadoop 2.8**
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Because of the nature of the S3 object store, data written to an S3A `OutputStream`
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@@ -1233,8 +1233,18 @@ consumed, and so eliminates heap size as the limiting factor in queued uploads
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<value>disk</value>
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</property>
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+<property>
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+ <name>fs.s3a.buffer.dir</name>
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+ <value></value>
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+ <description>Comma separated list of temporary directories use for
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+ storing blocks of data prior to their being uploaded to S3.
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+ When unset, the Hadoop temporary directory hadoop.tmp.dir is used</description>
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+</property>
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+
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```
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+This is the default buffer mechanism. The amount of data which can
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+be buffered is limited by the amount of available disk space.
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#### <a name="s3a_fast_upload_bytebuffer"></a>Fast Upload with ByteBuffers: `fs.s3a.fast.upload.buffer=bytebuffer`
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@@ -1248,7 +1258,7 @@ The amount of data which can be buffered is
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limited by the Java runtime, the operating system, and, for YARN applications,
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the amount of memory requested for each container.
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-The slower the write bandwidth to S3, the greater the risk of running out
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+The slower the upload bandwidth to S3, the greater the risk of running out
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of memory —and so the more care is needed in
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[tuning the upload settings](#s3a_fast_upload_thread_tuning).
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Mingliang Liu