Step 2: Create a table

Now that you have a database, you can create an Athena table for it. The table that you create will be based on sample Amazon CloudFront log data in the location s3://athena-examples-myregion/cloudfront/plaintext/, where myregion is your current Amazon Web Services Region.

The sample log data is in tab-separated values (TSV) format, which means that a tab character is used as a delimiter to separate the fields. The data looks like the following example. For readability, the tabs in the excerpt have been converted to spaces and the final field shortened.

2014-07-05 20:00:09 DFW3 4260 10.0.0.15 GET eabcd12345678.cloudfront.net /test-image-1.jpeg 200 - Mozilla/5.0[...]
2014-07-05 20:00:09 DFW3 4252 10.0.0.15 GET eabcd12345678.cloudfront.net /test-image-2.jpeg 200 - Mozilla/5.0[...]
2014-07-05 20:00:10 AMS1 4261 10.0.0.15 GET eabcd12345678.cloudfront.net /test-image-3.jpeg 200 - Mozilla/5.0[...]

To enable Athena to read this data, you could create a straightforward CREATE EXTERNAL TABLE statement like the following. The statement that creates the table defines columns that map to the data, specifies how the data is delimited, and specifies the Amazon S3 location that contains the sample data. Note that because Athena expects to scan all of the files in a folder, the LOCATION clause specifies an Amazon S3 folder location, not a specific file.

Do not use this example just yet as it has an important limitation that will be explained shortly.

CREATE EXTERNAL TABLE IF NOT EXISTS cloudfront_logs (
  `Date` DATE,
  Time STRING,
  Location STRING,
  Bytes INT,
  RequestIP STRING,
  Method STRING,
  Host STRING,
  Uri STRING,
  Status INT,
  Referrer STRING,
  ClientInfo STRING
  ) 
  ROW FORMAT DELIMITED
  FIELDS TERMINATED BY '\t'
  LINES TERMINATED BY '\n'
  LOCATION 's3://athena-examples-my-region/cloudfront/plaintext/';

The example creates a table called cloudfront_logs and specifies a name and data type for each field. These fields become the columns in the table. Because date is a reserved word, it is escaped with backtick (`) characters. ROW FORMAT DELIMITED means that Athena will use a default library called LazySimpleSerDe to do the actual work of parsing the data. The example also specifies that the fields are tab separated (FIELDS TERMINATED BY '\t') and that each record in the file ends in a newline character (LINES TERMINATED BY '\n). Finally, the LOCATION clause specifies the path in Amazon S3 where the actual data to be read is located.

If you have your own tab or comma-separated data, you can use a CREATE TABLE statement like the example just presented—as long as your fields do not contain nested information. However, if you have a column like ClientInfo that contains nested information that uses a different delimiter, a different approach is required.

Extracting data from the ClientInfo field

Looking at the sample data, here is a full example of the final field ClientInfo:

Mozilla/5.0%20(Android;%20U;%20Windows%20NT%205.1;%20en-US;%20rv:1.9.0.9)%20Gecko/2009040821%20IE/3.0.9

As you can see, this field is multivalued. Because the example CREATE TABLE statement just presented specifies tabs as field delimiters, it can't break out the separate components inside the ClientInfo field into separate columns. So, a new CREATE TABLE statement is required.

To create columns from the values inside the ClientInfo field, you can use a regular expression (regex) that contains regex groups. The regex groups that you specify become separate table columns. To use a regex in your CREATE TABLE statement, use syntax like the following. This syntax instructs Athena to use the Regex SerDe library and the regular expression that you specify.

ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.RegexSerDe'
  WITH SERDEPROPERTIES ("input.regex" = "regular_expression")

Regular expressions can be useful for creating tables from complex CSV or TSV data but can be difficult to write and maintain. Fortunately, there are other libraries that you can use for formats like JSON, Parquet, and ORC. For more information, see Supported SerDes and data formats.

Now you are ready to create the table in the Athena query editor. The CREATE TABLE statement and regex are provided for you.