Upload data to Amazon S3
For information on how to upload objects to Amazon S3, see Add an object to your
bucket in the Amazon Simple Storage Service User Guide. For more information
about using Amazon S3 with Hadoop, see http://wiki.apache.org/hadoop/AmazonS3
Topics
Create and configure an Amazon S3 bucket
Amazon EMR uses the AWS SDK for Java with Amazon S3 to store input data, log files, and output data. Amazon S3 refers to these storage locations as buckets. Buckets have certain restrictions and limitations to conform with Amazon S3 and DNS requirements. For more information, see Bucket restrictions and limitations in the Amazon Simple Storage Service User Guide.
This section shows you how to use the Amazon S3 AWS Management Console to create and then set permissions for an Amazon S3 bucket. You can also create and set permissions for an Amazon S3 bucket using the Amazon S3 API or AWS CLI. You can also use curl along with a modification to pass the appropriate authentication parameters for Amazon S3.
See the following resources:
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To create a bucket using the console, see Create a bucket in the Amazon S3 User Guide.
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To create and work with buckets using the AWS CLI, see Using high-level S3 commands with the AWS Command Line Interface in the Amazon S3 User Guide.
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To create a bucket using an SDK, see Examples of creating a bucket in the Amazon Simple Storage Service User Guide.
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To work with buckets using curl, see Amazon S3 authentication tool for curl
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For more information on specifying Region-specific buckets, see Accessing a bucket in the Amazon Simple Storage Service User Guide.
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To work with buckets using Amazon S3 Access Points, see Using a bucket-style alias for your access point in the Amazon S3 User Guide. You can easily use Amazon S3 Access Points with the Amazon S3 Access Point Alias instead of the Amazon S3 bucket name. You can use the Amazon S3 Access Point Alias for both existing and new applications, including Spark, Hive, Presto and others.
Note
If you enable logging for a bucket, it enables only bucket access logs, not Amazon EMR cluster logs.
During bucket creation or after, you can set the appropriate permissions to access the bucket depending on your application. Typically, you give yourself (the owner) read and write access and give authenticated users read access.
Required Amazon S3 buckets must exist before you can create a cluster. You must upload any required scripts or data referenced in the cluster to Amazon S3. The following table describes example data, scripts, and log file locations.
Configure multipart upload for Amazon S3
Amazon EMR supports Amazon S3 multipart upload through the AWS SDK for Java. Multipart upload lets you upload a single object as a set of parts. You can upload these object parts independently and in any order. If transmission of any part fails, you can retransmit that part without affecting other parts. After all parts of your object are uploaded, Amazon S3 assembles the parts and creates the object.
For more information, see Multipart upload overview in the Amazon Simple Storage Service User Guide.
In addition, Amazon EMR offers properties that allow you to more precisely control the clean-up of failed multipart upload parts.
The following table describes the Amazon EMR configuration properties for multipart
upload. You can configure these using the core-site
configuration
classification. For more information, see Configure applications in the
Amazon EMR Release Guide.
Configuration parameter name | Default value | Description |
---|---|---|
fs.s3n.multipart.uploads.enabled |
true |
A Boolean type that indicates whether to enable multipart
uploads. When EMRFS consistent view is enabled, multipart
uploads are enabled by default and setting this value to
false is ignored. |
fs.s3n.multipart.uploads.split.size |
134217728 |
Specifies the maximum size of a part, in bytes, before
EMRFS starts a new part upload when multipart uploads is
enabled. The minimum value is If EMRFS client-side encryption is disabled and the Amazon S3
Optimized Committer is also disabled, this value also
controls the maximum size that a data file can grow until
EMRFS uses multipart uploads rather than a
|
fs.s3n.ssl.enabled |
true |
A Boolean type that indicates whether to use http or https. |
fs.s3.buckets.create.enabled |
false |
A Boolean type that indicates whether a bucket should be
created if it does not exist. Setting to false
causes an exception on CreateBucket
operations. |
fs.s3.multipart.clean.enabled |
false |
A Boolean type that indicates whether to enable background periodic clean-up of incomplete multipart uploads. |
fs.s3.multipart.clean.age.threshold |
604800 |
A long type that specifies the minimum age of a multipart upload, in seconds, before it is considered for cleanup. The default is one week. |
fs.s3.multipart.clean.jitter.max |
10000 |
An integer type that specifies the maximum amount of random jitter delay in seconds added to the 15-minute fixed delay before scheduling next round of clean-up. |
Disable multipart uploads
Best practices
The following are recommendations for using Amazon S3 buckets with EMR clusters.
Enable versioning
Versioning is a recommended configuration for your Amazon S3 bucket. By enabling versioning, you ensure that even if data is unintentionally deleted or overwritten it can be recovered. For more information, see Using versioning in the Amazon Simple Storage Service User Guide.
Clean up failed multipart uploads
EMR cluster components use multipart uploads via the AWS SDK for Java with Amazon S3 APIs to write log files and output data to Amazon S3 by default. For information about changing properties related to this configuration using Amazon EMR, see Configure multipart upload for Amazon S3. Sometimes the upload of a large file can result in an incomplete Amazon S3 multipart upload. When a multipart upload is unable to complete successfully, the in-progress multipart upload continues to occupy your bucket and incurs storage charges. We recommend the following options to avoid excessive file storage:
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For buckets that you use with Amazon EMR, use a lifecycle configuration rule in Amazon S3 to remove incomplete multipart uploads three days after the upload initiation date. Lifecycle configuration rules allow you to control the storage class and lifetime of objects. For more information, see Object lifecycle management, and Aborting incomplete multipart uploads using a bucket lifecycle policy.
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Enable Amazon EMR's multipart cleanup feature by setting
fs.s3.multipart.clean.enabled
totrue
and tuning other cleanup parameters. This feature is useful at high volume, large scale, and with clusters that have limited uptime. In this case, theDaysAfterIntitiation
parameter of a lifecycle configuration rule may be too long, even if set to its minimum, causing spikes in Amazon S3 storage. Amazon EMR's multipart cleanup allows more precise control. For more information, see Configure multipart upload for Amazon S3.
Manage version markers
We recommend that you enable a lifecycle configuration rule in Amazon S3 to remove expired object delete markers for versioned buckets that you use with Amazon EMR. When deleting an object in a versioned bucket, a delete marker is created. If all previous versions of the object subsequently expire, an expired object delete marker is left in the bucket. While you are not charged for delete markers, removing expired markers can improve the performance of LIST requests. For more information, see Lifecycle configuration for a bucket with versioning in the Amazon Simple Storage Service User Guide.
Performance best practices
Depending on your workloads, specific types of usage of EMR clusters and applications on those clusters can result in a high number of requests against a bucket. For more information, see Request rate and performance considerations in the Amazon Simple Storage Service User Guide.