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Output to an Amazon S3 bucket

Prerequisites
Ensure that you have an Amazon S3 connection with the correct permissions to write to your target bucket.
Create a job writing into Amazon S3
Once you have fulfilled the prerequisites, you can create an INSERT job as follows:
CREATE SYNC JOB insert_into_s3
    START_FROM = BEGINNING
    FILE_FORMAT = (type = CSV)
    COMPRESSION = GZIP
    DATE_PATTERN = 'yyyy-MM-dd-HH-mm'
    RUN_INTERVAL = 1 MINUTE
    COMPUTE_CLUSTER = "Default Compute"
    AS INSERT INTO S3 s3_output_connection LOCATION = 's3://your-bucket-name/path/to/folder/'
    -- Use the SELECT statement to choose columns from the source and implement your business logic transformations.
    SELECT 
      column1 AS s3_column1, 
      MD5(column2) AS s3_column2 -- hash or mask columns using built-in functions
    FROM default_glue_catalog.your_schema.your_raw_data_table
    WHERE time_filter();
This example only demonstrates an example of all job options available when writing to Amazon S3.
Depending on your use case, you may want to configure a different set of options. For example, set the FILE_FORMAT to Parquet or the COMPRESSION to SNAPPY
For the full list of job options with syntax and detailed descriptions, see: Amazon S3 transformation job options​
For more details regarding the INSERT command syntax, see: INSERT​
Alter a job writing to Amazon S3
Certain job options are considered mutable, meaning that in some cases, you can run a SQL command to alter an existing transformation job rather than having to create a new one.
For example, take the job we created as an example earlier:
CREATE SYNC JOB insert_into_s3
    START_FROM = BEGINNING
    FILE_FORMAT = (type = CSV)
    COMPRESSION = GZIP
    DATE_PATTERN = 'yyyy-MM-dd-HH-mm'
    RUN_INTERVAL = 1 MINUTE
    COMPUTE_CLUSTER = "Default Compute"
    AS INSERT INTO S3 s3_output_connection LOCATION = 's3://your-bucket-name/path/to/folder/'
    -- Use the SELECT statement to choose columns from the source and implement your business logic transformations.
    SELECT 
      column1 AS s3_column1, 
      MD5(column2) AS s3_column2 -- hash or mask columns using built-in functions
    FROM default_glue_catalog.your_schema.your_raw_data_table
    WHERE time_filter();
If you wanted to keep the job as is but just change the cluster that is running the job, you can run the following command:
ALTER JOB insert_into_s3
    SET COMPUTE_CLUSTER = high_memory_cluster;
Note that some options such as RUN_INTERVAL or the FILE_FORMAT cannot be altered once the connection has been created.
To check which specific job options are mutable, see Amazon S3 transformation job options​
Drop a job writing to Amazon S3
If you no longer need a certain job, you can easily drop it with the following SQL command:
DROP JOB insert_into_s3;
For the full list of job options with descriptions, see: DROP JOB​

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Last modified 2mo ago