Teradata R Package Function Reference - 16.20 - NPath - Teradata R Package

Teradata® R Package Function Reference

prodname
Teradata R Package
vrm_release
16.20
created_date
February 2020
category
Programming Reference
featnum
B700-4007-098K

Description

The nPath function scans a set of rows, looking for patterns that you specify. For each set of input rows that matches the pattern, nPath produces a single output row. The function provides a flexible pattern-matching capability that lets you specify complex patterns in the input data and define the values that are output for each matched input set.

Usage

  td_npath_sqle (
      data1 = NULL,
      mode = NULL,
      pattern = NULL,
      symbols = NULL,
      result = NULL,
      filter = NULL,
      data2 = NULL,
      data3 = NULL,
      data1.partition.column = NULL,
      data2.partition.column = NULL,
      data3.partition.column = NULL,
      data1.order.column = NULL,
      data2.order.column = NULL,
      data3.order.column = NULL
  )

Arguments

data1

Required Argument.
Input table

data1.partition.column

Partition By columns for data1.
Values to this argument can be provided as list, if multiple columns are used for ordering.

data1.order.column

Order By columns for data1.
Values to this argument can be provided as list, if multiple columns are used for ordering.

mode

Required Argument.
Specifies the pattern-matching mode: OVERLAPPING: The function finds every occurrence of the pattern in the partition, regardless of whether it is part of a previously found match. Therefore, one row can match multiple symbols in a given matched pattern. NONOVERLAPPING: The function begins the next pattern search at the row that follows the last pattern match. This is the default behavior of many commonly used pattern matching utilities, including the UNIX grep utility. Permitted Values are: OVERLAPPING, NONOVERLAPPING

pattern

Required Argument.
Specifies the pattern for which the function searches. You compose pattern with the symbols that you define in the symbols argument, operators, and parentheses. Table describes the simplest patterns, which you can combine to form more complex patterns. When patterns have multiple operators, the function applies them in order of precedence, and applies operators of equal precedence from left to right. Table also shows operator precedence. To force the function to evaluate a subpattern first, enclose it in parentheses. To specify that a subpattern must appear a specific number of times, use the "Range-Matching Feature". For pattern matching details, refer to "Pattern Matching".

symbols

Required Argument.
Defines the symbols that appear in the values of the pattern and result arguments. The col_expr is an expression whose value is a column name, symbol is any valid identifier, and symbol_predicate is a SQL predicate (often a column name).
For example, the Symbols argument for analyzing website visits might look like this: symbols ( pagetype = "homepage" AS H, pagetype <> "homepage" AND pagetype <> "checkout" AS PP, pagetype = "checkout" AS CO ) The symbol is case-insensitive; however, a symbol of one or two uppercase letters is easy to identify in patterns. If col_expr represents a column that appears in multiple input tables, then you must qualify the ambiguous column name with its table name. For example: Symbols ( weblog.pagetype = "homepage" AS H, weblog.pagetype = "thankyou" AS T, ads.adname = "xmaspromo" AS X, ads.adname = "realtorpromo" AS R ) For more information about symbols that appear in the Pattern argument value, refer to "symbols". For more information about symbols that appear in the Result argument value, refer to "result: Applying Aggregate Functions".

result

Required Argument.
Defines the output columns. The col_expr is an expression whose value is a column name; it specifies the values to retrieve from the matched rows. The function applies aggregate_function to these values. For details, see "result: Applying Aggregate Functions". The function evaluates this argument once for every matched pattern in the partition (that is, it outputs one row for each pattern match).

filter

Optional Argument.
Specifies filters to impose on the matched rows. The function combines the filter expressions using the AND operator. The filter_expression syntax is: symbol_expression comparison_operator symbol_expression The two symbol expressions must be type-compatible. The symbol_expression syntax is: { FIRST | LAST }(column_with_expression OF [ANY](symbol[,...])). The column_with_expression cannot contain the operator AND or OR, and all its columns must come from the same input. If the function has multiple inputs, then column_with_expression and symbol must come from the same input. The comparison_operators can be <, >, <=, >=, =, or !=. This argument can improve or degrade npath performance, depending on several factors. For details, refer to "filters".

data2

Optional Argument.
Additional optional input table

data2.partition.column

Partition By columns for data2.
Values to this argument can be provided as list, if multiple columns are used for ordering.

data2.order.column

Order By columns for data2.
Values to this argument can be provided as list, if multiple columns are used for ordering.

data3

Optional Argument.
Additional optional input table

data3.partition.column

Partition By columns for data3.
Values to this argument can be provided as list, if multiple columns are used for ordering.

data3.order.column

Order By columns for data3.
Values to this argument can be provided as list, if multiple columns are used for ordering.

Value

Function returns an object of class "td_npath_sqle" which is a named list containing Teradata tbl object.
Named list member can be referenced directly with the "$" operator using name: result

Examples

    # Get the current context/connection
    con <- td_get_context()$connection
    
    # Load data
    loadExampleData("npath_example1", "bank_web_clicks2")
    
    # Create remote tibble objects.
    tblQuery <- "SELECT customer_id, session_id, datestamp, page FROM bank_web_clicks2"
    bank_web_clicks2 <- tbl(con, sql(tblQuery))
    
    # Execute npath function.
    npath_out <- td_npath_sqle(
                       data1=bank_web_clicks2,
                       data1.partition.column = c("customer_id", "session_id"),
                       data1.order.column = "datestamp",
                       mode = "nonoverlapping",
                       pattern = "(DUP|A)*",
                       symbols = c("true AS A",
                                   "page = LAG (page,1) AS DUP"),
                       result = c("FIRST (customer_id OF any (A)) AS customer_id",
                                  "FIRST (session_id OF A) AS session_id",
                                  "FIRST (datestamp OF A) AS first_date",
                                  "LAST (datestamp OF ANY(A,DUP)) AS last_date",
                                  "ACCUMULATE (page OF A) AS page_path",
                                  "ACCUMULATE (page of DUP) AS dup_path")
                       );