# 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](https://github.com/elastic/logstash/blob/v1.4.2/patterns/grok-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](https://github.com/elastic/logstash/blob/v1.4.2/patterns/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](https://docs.aws.amazon.com/AmazonS3/latest/userguide/LogFormat.html) `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 + [Understanding Grok Patterns](https://edgedelta.com/company/blog/what-are-grok-patterns) (external website) + [Built-in patterns](https://docs.aws.amazon.com/glue/latest/dg/custom-classifier.html#classifier-builtin-patterns) (*AWS Glue User Guide*)