Reading input files in larger groups - Amazon Glue
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Reading input files in larger groups

You can set properties of your tables to enable an Amazon Glue ETL job to group files when they are read from an Amazon S3 data store. These properties enable each ETL task to read a group of input files into a single in-memory partition, this is especially useful when there is a large number of small files in your Amazon S3 data store. When you set certain properties, you instruct Amazon Glue to group files within an Amazon S3 data partition and set the size of the groups to be read. You can also set these options when reading from an Amazon S3 data store with the create_dynamic_frame.from_options method.

To enable grouping files for a table, you set key-value pairs in the parameters field of your table structure. Use JSON notation to set a value for the parameter field of your table. For more information about editing the properties of a table, see Viewing and managing table details.

You can use this method to enable grouping for tables in the Data Catalog with Amazon S3 data stores.

groupFiles

Set groupFiles to inPartition to enable the grouping of files within an Amazon S3 data partition. Amazon Glue automatically enables grouping if there are more than 50,000 input files, as in the following example.


  'groupFiles': 'inPartition'
groupSize

Set groupSize to the target size of groups in bytes. The groupSize property is optional, if not provided, Amazon Glue calculates a size to use all the CPU cores in the cluster while still reducing the overall number of ETL tasks and in-memory partitions.

For example, the following sets the group size to 1 MB.


  'groupSize': '1048576'

Note that the groupsize should be set with the result of a calculation. For example 1024 * 1024 = 1048576.

recurse

Set recurse to True to recursively read files in all subdirectories when specifying paths as an array of paths. You do not need to set recurse if paths is an array of object keys in Amazon S3, or if the input format is parquet/orc, as in the following example.


  'recurse':True

If you are reading from Amazon S3 directly using the create_dynamic_frame.from_options method, add these connection options. For example, the following attempts to group files into 1 MB groups.


df = glueContext.create_dynamic_frame.from_options("s3", {'paths': ["s3://s3path/"], 'recurse':True, 'groupFiles': 'inPartition', 'groupSize': '1048576'}, format="json")
Note

groupFiles is supported for DynamicFrames created from the following data formats: csv, ion, grokLog, json, and xml. This option is not supported for avro, parquet, and orc.