Grok SerDe - Amazon Athena
Serialization library nameHow to use the Grok SerDeExamplesSee also

Grok SerDe

The Logstash Grok SerDe is a library with a set of specialized patterns for deserialization of unstructured text data, usually logs. Each Grok pattern is a named regular expression. You can identify and re-use these deserialization patterns as needed. This makes it easier to use Grok compared with using regular expressions. Grok provides a set of pre-defined patterns. You can also create custom patterns.

Serialization library name

The serialization library name for the Grok SerDe is com.amazonaws.glue.serde.GrokSerDe.

How to use the Grok SerDe

To specify the Grok SerDe when creating a table in Athena, use the ROW FORMAT SERDE 'com.amazonaws.glue.serde.GrokSerDe' clause, followed by the WITH SERDEPROPERTIES clause that specifies the patterns to match in your data, where:

  • The input.format expression defines the patterns to match in the data. This is required.

  • The input.grokCustomPatterns expression defines a named custom pattern, which you can subsequently use within the input.format expression. This is optional. To include multiple pattern entries into the input.grokCustomPatterns expression, use the newline escape character (\n) to separate them, as follows: 'input.grokCustomPatterns'='INSIDE_QS ([^\"]*)\nINSIDE_BRACKETS ([^\\]]*)').

  • The STORED AS INPUTFORMAT and OUTPUTFORMAT clauses are required.

  • The LOCATION clause specifies an Amazon S3 bucket, which can contain multiple data objects. All data objects in the bucket are deserialized to create the table.

Examples

The examples in this section rely on the list of predefined Grok patterns. For more information, see grok-patterns on GitHub.com.

Example 1

This example uses source data from Postfix maillog entries saved in s3://amzn-s3-demo-bucket/groksample/.

Feb  9 07:15:00 m4eastmail postfix/smtpd[19305]: B88C4120838: connect from unknown[192.168.55.4]
Feb  9 07:15:00 m4eastmail postfix/smtpd[20444]: B58C4330038: client=unknown[192.168.55.4]
Feb  9 07:15:03 m4eastmail postfix/cleanup[22835]: BDC22A77854: message-id=<31221401257553.5004389LCBF@m4eastmail.example.com>

The following statement creates a table in Athena called mygroktable from the source data, using a custom pattern and the predefined patterns that you specify:

CREATE EXTERNAL TABLE `mygroktable`(
   syslogbase string,
   queue_id string,
   syslog_message string
   )
ROW FORMAT SERDE
   'com.amazonaws.glue.serde.GrokSerDe'
WITH SERDEPROPERTIES (
   'input.grokCustomPatterns' = 'POSTFIX_QUEUEID [0-9A-F]{7,12}',
   'input.format'='%{SYSLOGBASE} %{POSTFIX_QUEUEID:queue_id}: %{GREEDYDATA:syslog_message}'
   )
STORED AS INPUTFORMAT
   'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
   'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
   's3://amzn-s3-demo-bucket/groksample/';

Start with a pattern like %{NOTSPACE:column} to get the columns mapped first, and then specialize the columns if needed.

Example 2

In the following example, you create a query for Log4j logs. The example logs have the entries in this format:

2017-09-12 12:10:34,972 INFO  - processType=AZ, processId=ABCDEFG614B6F5E49, status=RUN,
threadId=123:amqListenerContainerPool23P:AJ|ABCDE9614B6F5E49||2017-09-12T12:10:11.172-0700],
executionTime=7290, tenantId=12456, userId=123123f8535f8d76015374e7a1d87c3c, shard=testapp1,
jobId=12312345e5e7df0015e777fb2e03f3c, messageType=REAL_TIME_SYNC,
action=receive, hostname=1.abc.def.com

To query this log data:

  • Add the Grok pattern to the input.format for each column. For example, for timestamp, add %{TIMESTAMP_ISO8601:timestamp}. For loglevel, add %{LOGLEVEL:loglevel}.

  • Make sure the pattern in input.format matches the format of the log exactly, by mapping the dashes (-) and the commas that separate the entries in the log format.

    CREATE EXTERNAL TABLE bltest (
 timestamp STRING,
 loglevel STRING,
 processtype STRING,
 processid STRING,
 status STRING,
 threadid STRING,
 executiontime INT,
 tenantid INT,
 userid STRING,
 shard STRING,
 jobid STRING,
 messagetype STRING,
 action STRING,
 hostname STRING
 )
ROW FORMAT SERDE 'com.amazonaws.glue.serde.GrokSerDe'
WITH SERDEPROPERTIES (
"input.grokCustomPatterns" = 'C_ACTION receive|send',
"input.format" = "%{TIMESTAMP_ISO8601:timestamp} %{LOGLEVEL:loglevel} - processType=%{NOTSPACE:processtype}, processId=%{NOTSPACE:processid}, status=%{NOTSPACE:status}, threadId=%{NOTSPACE:threadid}, executionTime=%{POSINT:executiontime}, tenantId=%{POSINT:tenantid}, userId=%{NOTSPACE:userid}, shard=%{NOTSPACE:shard}, jobId=%{NOTSPACE:jobid}, messageType=%{NOTSPACE:messagetype}, action=%{C_ACTION:action}, hostname=%{HOST:hostname}"
) STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 's3://amzn-s3-demo-bucket/samples/';

Example 3

The following example Amazon S3 server access logs CREATE TABLE statement shows the 'input.grokCustomPatterns' expression that contains two pattern entries, separated by the newline escape character (\n), as shown in this snippet from the example query: 'input.grokCustomPatterns'='INSIDE_QS ([^\"]*)\nINSIDE_BRACKETS ([^\\]]*)').

CREATE EXTERNAL TABLE `s3_access_auto_raw_02`(
  `bucket_owner` string COMMENT 'from deserializer', 
  `bucket` string COMMENT 'from deserializer', 
  `time` string COMMENT 'from deserializer', 
  `remote_ip` string COMMENT 'from deserializer', 
  `requester` string COMMENT 'from deserializer', 
  `request_id` string COMMENT 'from deserializer', 
  `operation` string COMMENT 'from deserializer', 
  `key` string COMMENT 'from deserializer', 
  `request_uri` string COMMENT 'from deserializer', 
  `http_status` string COMMENT 'from deserializer', 
  `error_code` string COMMENT 'from deserializer', 
  `bytes_sent` string COMMENT 'from deserializer', 
  `object_size` string COMMENT 'from deserializer', 
  `total_time` string COMMENT 'from deserializer', 
  `turnaround_time` string COMMENT 'from deserializer', 
  `referrer` string COMMENT 'from deserializer', 
  `user_agent` string COMMENT 'from deserializer', 
  `version_id` string COMMENT 'from deserializer')
ROW FORMAT SERDE 
  'com.amazonaws.glue.serde.GrokSerDe' 
WITH SERDEPROPERTIES ( 
  'input.format'='%{NOTSPACE:bucket_owner} %{NOTSPACE:bucket} \\[%{INSIDE_BRACKETS:time}\\] %{NOTSPACE:remote_ip} %{NOTSPACE:requester} %{NOTSPACE:request_id} %{NOTSPACE:operation} %{NOTSPACE:key} \"?%{INSIDE_QS:request_uri}\"? %{NOTSPACE:http_status} %{NOTSPACE:error_code} %{NOTSPACE:bytes_sent} %{NOTSPACE:object_size} %{NOTSPACE:total_time} %{NOTSPACE:turnaround_time} \"?%{INSIDE_QS:referrer}\"? \"?%{INSIDE_QS:user_agent}\"? %{NOTSPACE:version_id}', 
  'input.grokCustomPatterns'='INSIDE_QS ([^\"]*)\nINSIDE_BRACKETS ([^\\]]*)') 
STORED AS INPUTFORMAT 
  'org.apache.hadoop.mapred.TextInputFormat' 
OUTPUTFORMAT 
  'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
  's3://amzn-s3-demo-bucket'

See also