Redshift Spectrum: Automatically partition tables by date/folder

Question

We currently generate a daily CSV export that we upload to an S3 bucket, into the following structure:

<report-name>
|--reportDate-<date-stamp>
    |-- part0.csv.gz
    |-- part1.csv.gz

We want to be able to run reports partitioned by daily export.

According to this page, you can partition data in Redshift Spectrum by a key which is based on the source S3 folder where your Spectrum table sources its data. However, from the example, it looks like you need an ALTER statement for each partition:

alter table spectrum.sales_part
add partition(saledate='2008-01-01') 
location 's3://bucket/tickit/spectrum/sales_partition/saledate=2008-01/';

alter table spectrum.sales_part
add partition(saledate='2008-02-01') 
location 's3://awssampledbuswest2/tickit/spectrum/sales_partition/saledate=2008-02/';

Is there any way to set the table up so that data is automatically partitioned by the folder it comes from, or do we need a daily job to ALTER the table to add that day's partition?

Answer 1

Solution 1:

At max 20000 partitions can be created per table. You can create a one-time script to add the partitions (at max 20k) for all the future s3 partition folders.

For eg.

If folder s3://bucket/ticket/spectrum/sales_partition/saledate=2017-12/ doesn't exist, you can even add partition for that.

alter table spectrum.sales_part
add partition(saledate='2017-12-01') 
location 's3://bucket/tickit/spectrum/sales_partition/saledate=2017-12/';

Solution 2:

https://aws.amazon.com/blogs/big-data/data-lake-ingestion-automatically-partition-hive-external-tables-with-aws/