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Consumption Analytics Documentation

Home > Cloud Cruiser 4 > Collecting, transforming, and publishing > Steps for all collectors > Lookups > Managing lookup tables using flat files

Managing lookup tables using flat files

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For large tables with hundreds or thousands of entries, it might be more efficient to use flat files instead of the Cloud Cruiser UI because you can automate their maintenance with an external application or script. Another reason to use a flat file table is that you can provide a single pattern to match rather than a range of values.

There are no revisions for a flat file translation table. Comparisons are made against the contents of the file at the time a job runs.

Format

Flat file translation tables use the following comma-delimited format where pattern is an exact pattern to match:

pattern,lowId,highId,targetValue

You must include either a pattern or both lowId and highId against which to compare input values. If both are provided, pattern takes precedence and the low and high values are not used. You can use an asterisk in a pattern as a wildcard to represent multiple characters. For example:

  • The pattern abc matches only "abc"
  • The pattern abc* matches any value starting with "abc," such as “abcdef”

Using the cc_table example described in Using lookup tables, its entries in a CSV file would be represented as:

,aa,az,Customer A
,ba,bz,Customer A
,,,Customer A

Using in a job

To use a flat file translation table, in your batch job include the lookupFile propertyof an applicable transform processor to reference the file rather than the translateTitle property to reference a table maintained in the Cloud Cruiser UI. For example:

<bean class="com.cloudcruiser.batch.transform.CreateIdentifierFromTable">
  <property name="active" value="true" />
  <property name="lookupFile" value="file:${env.usageDir}/cc_table.csv"/>
  <property name="sourceIdentifier" value="host" />
  ...
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