Once you execute query it generates CSV file. Let's see how we can load CSV data from S3 into Glue data catalog using Glue crawler and run SQL query on the data in Athena. Select the database in the sidebar once it’s created. But you can use any existing bucket as well. Amazon Athena is a serverless AWS query service which can be used by cloud developers and analytic professionals to query data of your data lake stored as text files in Amazon S3 buckets folders. This post outlines some steps you would need to do to get Athena parsing your files correctly. Results are also written as a CSV file to an S3 bucket; by default, results go to s3://aws-athena-query-results--region/. I am trying to read csv file from s3 bucket and create a table in AWS Athena. You’ll get an option to create a table on the Athena home page. Create a table in Athena from a csv file with header stored in S3. Let's walk through it step by step. Up to this point, I was thrilled with the Athena experience. Mine looks something similar to the screenshot below, because I already have a few tables. Once you have the file downloaded, create a new bucket in AWS S3. Click “Create Table,” and select “from S3 Bucket Data”: Upload your data to S3, and select “Copy Path” to get a link to it. Click “Create Table,” and select “from S3 Bucket Data”: Upload your data to S3, and select “Copy Path” to get a link to it. I suggest creating a new bucket so that you can use that bucket exclusively for trying out Athena. Step3-Read data from Athena Query output files (CSV / JSON stored in S3 bucket) When you create Athena table you have to specify query output folder and data input location and file format (e.g. You’ll want to create a new folder to store the file in, even if you only have one file, since Athena … So, now that you have the file in S3, open up Amazon Athena. Select the database in the sidebar once it’s created. You can change the bucket by clicking Settings in the Athena UI. You’ll want to create a new folder to store the file in, even if you only have one file, since Athena … For this post, we’ll stick with the basics and select the “Create table from S3 bucket data” option.So, now that you have the file in S3, open up Amazon Athena. Thanks to the Create Table As feature, it’s a single query to transform an existing table to a table backed by Parquet. You’ll get an option to create a table on the Athena home page. CSV, JSON, Avro, ORC, Parquet …) they can be GZip, Snappy Compressed. The next step, creating the table, is more interesting: not only does Athena create the table, but it also learns where and how to read the data from my S3 … My table when created is unable to skip the header information of my CSV file. Create External Table in Amazon Athena Database to Query Amazon S3 Text Files. Query results can be downloaded from the UI as CSV files. Have you thought of trying out AWS Athena to query your CSV files in S3? 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