python

Getting started with Amazon Timestream with Python

This sample application shows how you can create a database and table, populate the table with ~126K rows of sample data, and run sample queries to jumpstart your evaluation and/or proof-of-concept applications with Amazon Timestream.

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How to use it

1. Install and configure Boto3 set up following the instructions at https://boto3.amazonaws.com/v1/documentation/api/latest/index.html

   pip install boto3
   

2. Install Pandas and its associated dependencies for reading parquet files from S3

   pip install pandas pyarrow s3fs
   

3. Run the following commands to insert data into Timestream and to query the data

   python SampleApplication.py -t basic --csv_file_path ../data/sample.csv --kmsId ${kmsId}
   

   Both --kmsId and --csv_file_path are optional parameters.

   UpdateDatabase API will be called if the kmsId is provided. This kmsId should refer to a valid kms key present in your account. If the kmsId is not provided, UpdateDatabase will not be called.

   Data ingestion through csv file will happen if csv_file_path is provided.

4. Run the following commands to insert data into Timestream and export the data into S3 using Unload

   python SampleApplication.py -t unload --csv_file_path ../data/sample_unload.csv
   

5. Run the following command to run sample application for composite partition key:

   python SampleApplication.py -t composite_partition_key