Amazon Athena was one of a few new big Data Services announced at re:Invent 2016 Along with AWS Glue, And GreenGrass (which was more of an IOT offering).If you are interacting with Apache Spark, then your table column names must be lowercase.Īthena is case insensitive but Spark requires lowercase table names.Īthena table names only allow the underscore characterĪthena table names cannot contain any special characters beside the underscore _ In the LOCATION clause, use a trailing slash for your folder, NOT filenames or glob characters For example:įor the location clause, use a trailing slash Use backticks if table names begin with an underscore. Table names that begin with an underscore Understanding of what colums are there so you can create theĪthena table before you can start querying When looking through your S3 buckets and finding one of the allowedįormats (CSV, TSV, Parquet, etc) you will have to have an You will need to have some understanding of the structure of yourĭata or have a DDL meta store before you can start querying with LOCATION 's3://athena-examples/elb/plaintext/' įor more information Read the documentation page for Catalog Management WITH SERDEPROPERTIES ( 'serialization.format' = '1', `url` string, `protocol` string, `user_agent` string, `ssl_cipher` string, `ssl_protocol` string ) `received_bytes` bigint, `sent_bytes` bigint, `request_verb` string, `elb_response_code` string, `backend_response_code` string, `backend_processing_time` double, `client_response_time` double, `backend_port` int, `request_processing_time` double, Less I/O = Better performance & more cost savingsĬREATE EXTERNAL TABLE IF NOT EXISTS default.elb_logs ( `request_timestamp` string,. Use Compressed Formats: Snappy, Zlib, GZIP ( no LZO) (SQL Workbench, Agility, Aqua Data Studio)ĭownloads/drivers/AthenaJDBC41-1.0.0.jar.Īws s3 cp s3://athena-downloads/drivers/AthenaJDBC41-1.0.0.jar [loc It can run multiple queries in parallel.Run queries straight from the AWS Console LZO is not supported (use Snappy instead).Any Transaction found on Hive or Presto.Service based on Presto (which is available in Amazon EMR) Queries execute in parallel – so results are FAST, even with large datasets and complex.S3 data is never modified (data is loaded in read only memory).No charge for Data Definition Language Statements (DDL) WITHOUT the need to CREATE, MANAGE, or worrying about Scaling Querying Data in S3 with out the need for EMRīig Data Offerings Announced at re:Invent 2016Īthena allows you to Run interactive SQL Queries on S3 data
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