You’ll get an option to create a table on the Athena home page. Results are also written as a CSV file to an S3 bucket; by default, results go to s3://aws-athena-query-results--region/. Once you have the file downloaded, create a new bucket in AWS S3. This post outlines some steps you would need to do to get Athena parsing your files correctly. I am trying to read csv file from s3 bucket and create a table in AWS Athena. So, now that you have the file in S3, open up Amazon Athena. You’ll want to create a new folder to store the file in, even if you only have one file, since Athena … My table when created is unable to skip the header information of my CSV file. 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. You’ll get an option to create a table on the Athena home page. 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. Query results can be downloaded from the UI as CSV files. Mine looks something similar to the screenshot below, because I already have a few tables. 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. Create a table in Athena from a csv file with header stored in 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. You can change the bucket by clicking Settings in the Athena UI. Up to this point, I was thrilled with the Athena experience. Select the database in the sidebar once it’s created. I suggest creating a new bucket so that you can use that bucket exclusively for trying out Athena. CSV, JSON, Avro, ORC, Parquet …) they can be GZip, Snappy Compressed. - amazon_athena_create_table.ddl Have you thought of trying out AWS Athena to query your CSV files in S3? Once you execute query it generates CSV file. Click “Create Table,” and select “from S3 Bucket Data”: Upload your data to S3, and select “Copy Path” to get a link to it. Select the database in the sidebar once it’s created. Create External Table in Amazon Athena Database to Query Amazon S3 Text Files. Thanks to the Create Table As feature, it’s a single query to transform an existing table to a table backed by Parquet. Let's walk through it step by step. To demonstrate this feature, I’ll use an Athena table querying an S3 bucket with ~666MBs of raw CSV files (see Using Parquet on Athena to Save Money on AWS on how to create the table (and learn the benefit of using Parquet)). 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