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MATCHES Function

Returns true if a value contains a string or pattern. The value to search can be a string literal, a function returning a string, or a reference to a column of String type. You can also search an array of columns.

Since the MATCHES function returns a Boolean value, it can be used as both a function and as a conditional.

Tip

When you select values in a histogram for a column of Array type, the function that identifies the values on which to perform a transform is typically MATCHES.

Tip

If you need the location of the matched string within the source, use the FIND function. See FIND Function.

Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

Basic Usage

Column reference example:

matches(ProdId, 'Fun Toy')

Output: Returns true when the value in the ProdId column value contains the string literal Fun Toy.

matches([ProdId,ProdName], 'Fun Toy')

Output: Returns true when the value in the ProdId or ProdName column values contain the string literal Fun Toy.

String literal example:

matches('Hello, World', 'Hello')

Output: Returns true.

Syntax and Arguments

matches(column_string,string_pattern <span>[,ignore_case]</span>)

Argument

Required?

Data Type

Description

column_string

Y

string

Name of column or string literal to be searched. This value can also be an array of column names to search, combined in a logical OR.

string_pattern

Y

string

Name of column, function returning a string ,or string literal or pattern to find

ignore_case

N

string

Whentrue, matching is case-insensitive. Default isfalse.

For more information on syntax standards, see Language Documentation Syntax Notes.

column_string

Name of the column or string literal to be searched.

  • Missing string or column values generate missing string results.

    • String constants must be quoted ('Hello, World').

  • Multiple columns can be specified as an array ( matches([Col1,Col2],'hello').

Usage Notes:

Required?

Data Type

Example Value

Yes

String

MyColumn

string_pattern

Column of strings, function returning a string, or string literal. Value can be a column reference, string literal, Wrangle , or regular expression to match against the source column-string.

Usage Notes:

Required?

Data Type

Example Value

Yes

Column reference or string literal or pattern

'home page'

ignore_case

When true, matches are case-insensitive. Default is false.

Note

This argument is not required. By default, matches are case-sensitive.

Required?

Data Type

Example Value

No

String literal evaluating to a Boolean

'true'

Examples

Tip

For additional examples, see Common Tasks.

Example - Filtering log data

In downloaded log files, you might see error messages of the following type:

  • INFO - status information on the process

  • WARNING - system encountered a non-fatal error during execution

  • ERROR - system encountered an error, which might have caused the job to fail.

For purposes of analysis, you might want to filter out the data for INFO and WARNING messages.

Source:

Here is example data from a log file of a failed job:

log

2016-01-29T00:14:24.924Z com.example.hadoopdata.monitor.spark_runner.ProfilerServiceClient [pool-13-thread-1] INFO com.example.hadoopdata.monitor.spark_runner.BatchProfileSparkRunner - Spark Profiler URL - http://localhost:4006/

2016-01-29T00:14:40.066Z com.example.hadoopdata.monitor.spark_runner.BatchProfileSparkRunner [pool-13-thread-1] INFO com.example.hadoopdata.monitor.spark_runner.BatchProfileSparkRunner - Spark process ID was null.

2016-01-29T00:14:40.067Z com.example.hadoopdata.monitor.spark_runner.BatchProfileSparkRunner [pool-13-thread-1] INFO com.example.hadoopdata.monitor.spark_runner.BatchProfileSparkRunner - --------------------------------END SPARK JOB-------------------------------

2016-01-29T00:14:44.961Z com.example.hadoopdata.joblaunch.server.BatchPollingWorker [pool-4-thread-2] ERROR com.example.hadoopdata.joblaunch.server.BatchPollingWorker - Job '128' threw an exception during execution

2016-01-29T00:14:44.962Z com.example.hadoopdata.joblaunch.server.BatchPollingWorker [pool-4-thread-2] INFO com.example.hadoopdata.joblaunch.server.BatchPollingWorker - Making sure async worker is stopped

2016-01-29T00:14:44.962Z com.example.hadoopdata.joblaunch.server.BatchPollingWorker [pool-4-thread-2] INFO com.example.hadoopdata.joblaunch.server.BatchPollingWorker - Notifying monitor for job '128', code 'FAILURE'

2016-01-29T00:14:44.988Z com.example.hadoopdata.monitor.client.MonitorClient [pool-4-thread-2] INFO com.example.hadoopdata.monitor.client.MonitorClient - Request succeeded to monitor ip-0-0-0-0.example.com:8001

Transformation:

When the above data is loaded into the application, you might want to break up the data into separate columns, which splits them on the Z character at the end of the timestamp:

Transformation Name

Split column

Parameter: Column

column1

Parameter: Option

On pattern

Parameter: Match pattern

`Z `

Then, you can rename the two columns: Timestamp and Log_Message. To filter out the INFO and WARNING messages, you can use the following transforms, which match on the string literals to identify these messages:

Transformation Name

Filter rows

Parameter: Condition

Custom formula

Parameter: Type of formula

Custom single

Parameter: Condition

matches(Log_Message, '] INFO ')

Parameter: Action

Delete matching rows

Transformation Name

Filter rows

Parameter: Condition

Custom formula

Parameter: Type of formula

Custom single

Parameter: Condition

matches(Log_Message, '] WARNING ')

Parameter: Action

Delete matching rows

Results:

After the above steps, the data should look like the following:

Timestamp

Log_Message

2016-01-29T00:14:44.961

com.example.hadoopdata.joblaunch.server.BatchPollingWorker [pool-4-thread-2] ERROR com.example.hadoopdata.joblaunch.server.BatchPollingWorker - Job '128' threw an exception during execution