Returns the index value in the input string where a specified matching string is located in provided column, string literal, or function returning a string. Search is conducted left-to-right.

You can also search a string from the right. For more information, see RIGHTFIND Function.

Column reference example:

find(MyName,'find this',true,0)


Output
: Searches the MyName column value for the string find this from the beginning of the value, ignoring case. If a match is found, the index value where the string is located is returned. 

String literal example:

find('Hello, World','lo',false,2)

Output: Searches the string Hello, World for the string lo, in a case-sensitive search, beginning at the third character in the string. Since the match is found at the fourth character, the value 3 is returned.

If example:

if(find(SearchPool,'FindIt') >= 0, 'found it', '')


Output
: Searches the SearchPool column value for the string FindIt from the beginning of the value (default). Default behavior is to not ignore case. If the string is found, the value found it is returned. Otherwise, the column is empty.

find(string_to_search, search_for,[ignore_case], [start_at])


ArgumentRequired?Data TypeDescription
string_to_searchYstring

Name of the column, function returning a string, or string literal to be applied to the function.

search_forYstring

The string or pattern you want to look for. This can be a string, function returning a string, or string literal or pattern or regular expression.

ignore_caseNbooleanIndicates if the Find function ignores case when trying to match the string or pattern. The default value is false.
start_atNinteger (non-negative)

Indicates the position in the column or string literal value at which to begin the search. This value can be an integer, a function returning an integer, or a column containing integers. The default value is 0.

If not specified, the entire string is searched.

string_to_search

Name of the item to be searched. Valid values can be:

Missing values generate the start-at parameter value.

Required?Data TypeExample Value
YesString literal, function returning a string, or column reference (String, Array, or Object)myColumn

search_for

Column of strings, function returning a string, string literal or pattern to find. An input value can be a literal, , or a regular expression.

Required?Data TypeExample Value
YesString literal or pattern'Hello'

ignore_case

If true, the FIND function ignores case when trying to match the string literal or pattern value.

Default value is false, which means that case-sensitive matching is performed by default.


Required?Data TypeExample Value
NoBooleantrue

start_at

Indicates the position in the column or string literal value at which to begin the search. For example, a value of 2 instructs the FIND function to begin searching from the third character in the column or string value.

NOTE: Index values begin at 0. If not specified, the default value is 0, which searches the entire string.

Required?Data TypeExample Value
NoInteger (non-negative)2

Example - Locate product purchases in transaction stream

Source:

You have the simplified transaction stream listed below in which master information about a transaction (TransactionId and CustomerId) is paired with order detail information that is brought into the application as an array in the OrderDetail column. The array column contains information about product ID, quantity, and the type of transaction. 

TransactionIdCustomerIdOrderDetail
12312312100023[{"ProdId":"54321","Qty":"5","TransType":"PURCHASE"}]
12312313100045[{"ProdId":"94105","Qty":"12","TransType":"PURCHASE"}]
12312314100066[{"ProdId":"54321","Qty":"1","TransType":"TEST"}]
12312315100068[{"ProdId":"85858","Qty":"9","TransType":"PURCHASE"}]

The transaction stream includes test transactions, which are identified by the value TEST for TransType in the detail column. You want to remove these transactions early in the process, which should simplify your dataset and speed up its processing.

Transformation:

First, you must identify the records that contain the test transaction value. The following transform generates a new column containing true/false values for whether the value "TEST" appears in the OrderDetail transform.

Tip: You should include the double-quotes around the value, in case the other fields in the array could contain some version of the value TEST. Note that the double quotes need to be escaped, as in the value below.

When the step is added to the recipe, the find_OrderDetail column is generated, containing the index value returned by the FIND function. In this case, there is only one row that contains a value: 53 for the third transaction.

TransactionIdCustomerIdOrderDetailfind_OrderDetail
12312312100023[{"ProdId":"54321","Qty":"5","TransType":"PURCHASE"}]
12312313100045[{"ProdId":"94105","Qty":"12","TransType":"PURCHASE"}]
12312314100066[{"ProdId":"54321","Qty":"1","TransType":"TEST"}]53
12312315100068[{"ProdId":"85858","Qty":"9","TransType":"PURCHASE"}]

You can then add the following step to keep the rows where the FIND function returned a null value in the find_OrderDetail column:

Results:

TransactionIdCustomerIdOrderDetailfind_OrderDetail
12312312100023[{"ProdId":"54321","Qty":"5","TransType":"PURCHASE"}] 
12312313100045[{"ProdId":"94105","Qty":"12","TransType":"PURCHASE"}] 
12312315100068[{"ProdId":"85858","Qty":"9","TransType":"PURCHASE"}] 

You can delete the find_OrderDetail column at this time.