{"id":3028,"date":"2021-10-26T18:48:05","date_gmt":"2021-10-26T13:18:05","guid":{"rendered":"https:\/\/staging.encaptechno.com\/blog\/?p=3028"},"modified":"2024-05-17T17:38:48","modified_gmt":"2024-05-17T12:08:48","slug":"amazon-athena","status":"publish","type":"post","link":"https:\/\/staging.encaptechno.com\/blog\/amazon-athena\/","title":{"rendered":"What is Amazon Athena and How It Works?"},"content":{"rendered":"

\"What<\/a><\/b><\/p>\n

The process of analyzing data is somewhat complex in nature and includes multiple steps for simplifying things for which many tools are available. Amazon comes to the rescue by providing a service with the name of Amazon Athena that helps in analyzing data.<\/span><\/p>\n

Amazon Athena is a <\/span>serverless analytics tool<\/b> that allows users to query the data from S3 using the standard SQL syntax. As a leader in the world of cloud computing, AWS offers a wide range of services that offer competitive performance and affordable solutions used for running workloads as compared to on-premise architecture.<\/span><\/p>\n

AWS Athena is a service from the analytics domain that focuses on the retrieval of static data that is stored in S3 buckets using the standard SQL statements. It can be considered as a robust tool that helps customers to gain important insights on their data stored on S3 because it is serverless and there is no infrastructure for managing.<\/span><\/p>\n

<\/span>What is Amazon Athena?<\/b><\/span><\/h2>\n

Amazon launched Athena as an important service on 20<\/span>th<\/span> November 2016. It was launched as a serverless query service that was meant to make an analysis of data, using the standard SQL stored in Amazon S3 simpler. With just a few simple clicks in the AWS Management Console, the customers can easily point Amazon Athena at their data stored in Amazon S3 while running queries using standard SQL for generating results in seconds.\u00a0\u00a0\u00a0<\/span><\/p>\n

With the <\/span>interactive analytics service<\/b> of Amazon Athena, there is no infrastructure for setting up or managing and the customers pay only for the queries that they want to run. It scales automatically while executing queries in parallel which eventually gives quick results even with a huge dataset and complex queries.<\/span><\/p>\n

Athena uses a distributed SQL engine called Presto which is useful in running the SQL queries. It is based on the popular open-source technology called Hive which further helps in storing structured, unstructured, and semi-structured data. The Apache Hive data warehouse software facilitates the reading, writing, and managing of large datasets that reside in the distributed storage using SQL.<\/span><\/p>\n

There is a simple data pipeline in which data from different sources is fetched and dumped into the S3 buckets. This is raw data which means there are no transformations applied to the data yet. At this time, Amazon Athena can be used for connecting to this data in S3 while being analyzed. This is a simple process because you do not need to set up any database or external tools to query the raw data. After you are done with the analysis and finding out desired results, an EMR cluster can be used for running the complex analytical data transformations while the data gets cleaned, processed, and stored.<\/span><\/p>\n

<\/span>Why Should You Use Athena?<\/b><\/span><\/h2>\n

\"Why<\/a>
\n<\/b><\/p>\n

An Athena user can query the encrypted data with keys managed by AWS key management service and also encrypt the query results. In fact, Athena also allows cross-account access to S3 buckets owned by another user. It uses managed data catalogs for storing information and schemas related to searches on Amazon S3 data.<\/span><\/p>\n

All in all, the interactive query service is actually an analytical tool that helps organizations in quickly analyzing important data stored in Amazon S3. It can be used in processing unstructured, structured, and semi structured data sets. With the use of Athena, it is possible to create dynamic queries for data sets. It works with the AWS Glue for giving you a much better way to store metadata in S3.<\/span><\/p>\n

Using the AWS Cloud Formation and Athena, you can use named queries that enable you to name a specific query and then also call it using the name. This is an interactive service from AWS that can be used by Data Scientists and developers for taking a peek into the table of running the query. It helps in fetching data from S3 and loads it to different datastores using the Athena JDBC driver for the log store analysis and Data Warehousing events.<\/span><\/p>\n

<\/span>Working of AWS Athena<\/b><\/span><\/h2>\n

Amazon Athena works in direct association with the S3 data. It is used as a distributed SQL engine for running the queries and it also uses Apache Hive for creating and altering tables and partitions. Some of the important standpoints needed for working with Athena include:<\/span><\/p>\n

    \n
  1. You must have an AWS Account<\/span><\/li>\n
  2. You should enable your account to export the cost and usage data into the S3 bucket.<\/span><\/li>\n
  3. You can prepare buckets for Athena to connect.<\/span><\/li>\n
  4. AWS also creates manifest files with the use of metadata each time it writes to the bucket. In fact, it creates a folder within the technology AWS billing data bucket known as Athena that contains only the data.<\/span><\/li>\n
  5. For simplifying the setup, a region called the US-West-2 region can also be used.<\/span><\/li>\n
  6. The last and final step is downloading the credentials for the new user because the credentials help indirectly mapping to the database credentials.<\/span><\/li>\n<\/ol>\n

    Amazon also offers a tool called Cost Explorer for dragging and dropping which comes with a set of pre-built reports such as Monthly service cost, reserved instance usage, etc. In case you are curious, you should try and recreate the query above the service costs and operation. This is in fact not impossible. You can slice the raw data while computing the growth rates each, building histograms, computing scores, etc.<\/span><\/p>\n

    Some of the additional considerations to note while working with Amazon Athena include:<\/span><\/p>\n

    <\/span>Pricing Model <\/b><\/span><\/h4>\n

    The pricing of Athena is over $5 for scanning Terabyte data from S3 surrounded to the closest megabyte having a minimum of 10MB per query.<\/span><\/p>\n

    <\/span>Reducing Cost<\/b><\/span><\/h4>\n

    The trick is reducing the data that is scanned in three ways called compressing data, using columnar data, and partitioning the data.<\/span><\/p>\n

    <\/span>Features of Athena<\/b><\/span><\/h2>\n

    Out of the many services provided by Amazon, Athena is one of the best services. It has multiple features that make it suitable for Data Analysis. Some of the features include:<\/span><\/p>\n