Teradata Package for R Function Reference | 17.20 - StringSimilarity - Teradata Package for R - Look here for syntax, methods and examples for the functions included in the Teradata Package for R.

Teradata® Package for R Function Reference

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for R
Release Number
17.20
Published
March 2024
Language
English (United States)
Last Update
2024-05-03
dita:id
TeradataR_FxRef_Enterprise_1720
Product Category
Teradata Vantage

StringSimilarity

Description

td_string_similarity_sqle() function calculates the similarity between two strings, using either the Jaro, Jaro-Winkler, N-Gram, or Levenshtein distance.

Usage

  td_string_similarity_sqle (
      data = NULL,
      comparison.columns = NULL,
      case.sensitive = NULL,
      accumulate = NULL,
      ...
  )

Arguments

data

Required Argument.
Specifies the input tbl_teradata.
Types: tbl_teradata

comparison.columns

Required Argument.
Specifies pairs of input tbl_teradata columns that contain strings to be compared (column1 and column2), how to compare them (comparison_type), and (optionally) a constant and the name of the output column for their similarity (output_column). The similarity is a value in the range [0, 1].
For comparison_type, use one of these values:

  • "jaro": Jaro distance.

  • "jaro_winkler": Jaro-Winkler distance (1 for an exact match, 0 otherwise). If you specify this comparison type, you can specify the value of factor p with constant. 0 ≤ p ≤ 0.25.
    Default: p = 0.1

  • "n_gram": N-gram similarity. If you specify this comparison type, you can specify the value of N with constant. Default: N = 2

  • "LD": Levenshtein distance The number of edits needed to transform one string into the other, where edits include insertions, deletions, or substitutions of individual characters.

  • "LDWS": Levenshtein distance without substitution. Number of edits needed to transform one string into the other using only insertions or deletions of individual characters.

  • "OSA": Optimal string alignment distance. Number of edits needed to transform one string into the other. Edits are insertions, deletions, substitutions, or transpositions of characters. A substring can be edited only once.

  • "DL": Damerau-Levenshtein distance. Like OSA, except that a substring can be edited any number of times.

  • "hamming": Hamming distance. Number of positions where corresponding characters differ (that is, minimum number of substitutions needed to transform one string into the other) for strings of equal length, otherwise -1 for strings of unequal length.

  • "LCS": Longest common substring. Length of longest substring common to both strings.

  • "jaccard": Jaccard index-based comparison.

  • "cosine": Cosine similarity.

  • "soundexcode": Only for English strings. -1 if either string has a non-English character, otherwise, 1 if their soundex codes are the same and 0 otherwise.

You can specify a different comparison_type for every pair of columns.
The default output_column is "sim_i", where i is the sequence number of the column pair.
Types: character OR vector of Strings (character)

case.sensitive

Optional Argument.
Specifies whether string comparison is case-sensitive. The default value is FALSE. You can specify either one value for all pairs or one value for each pair. If you specify one value for each pair, then the ith value applies to the ith pair.
Types: logical OR vector of logical

accumulate

Optional Argument.
Specifies the names of input tbl_teradata columns to be copied to the output.
Types: character OR vector of Strings (character)

...

Specifies the generic keyword arguments SQLE functions accept.
Below are the generic keyword arguments:

persist:
Optional Argument.
Specifies whether to persist the results of the function in a table or not.
When set to TRUE, results are persisted in a table; otherwise, results are garbage collected at the end of the session.
Default Value: FALSE
Types: logical

volatile:
Optional Argument.
Specifies whether to put the results of the function in a volatile table or not.
When set to TRUE, results are stored in a volatile table, otherwise not.
Default Value: FALSE
Types: logical

Function allows the user to partition, hash, order or local order the input data. These generic arguments are available for each argument that accepts tbl_teradata as input and can be accessed as:

  • "<input.data.arg.name>.partition.column" accepts character OR vector of Strings (character) (Strings)

  • "<input.data.arg.name>.hash.column" accepts character OR vector of Strings (character) (Strings)

  • "<input.data.arg.name>.order.column" accepts character OR vector of Strings (character) (Strings)

  • "local.order.<input.data.arg.name>" accepts logical

Note:
These generic arguments are supported by tdplyr if the underlying SQL Engine function supports, else an exception is raised.

Value

Function returns an object of class "td_string_similarity_sqle" which is a named list containing object of class "tbl_teradata".
Named list member(s) can be referenced directly with the "$" operator using the name(s):result

Examples

  
    
    # Get the current context/connection.
    con <- td_get_context()$connection
    
    # Load the example data.
    loadExampleData("stringsimilarity_example", "strsimilarity_input")
    
    # Create tbl_teradata object.
    strsimilarity_input <- tbl(con, "strsimilarity_input")
    
    # Check the list of available analytic functions.
    display_analytic_functions()
    
    # Example 1: Creating tbl_teradata by calculating the
    #            similarity between two strings.
    obj <- td_string_similarity_sqle(
            data = strsimilarity_input,
            comparison.columns=c('jaro (src_text1, tar_text) AS jaro1_sim',
                                 'LD (src_text1, tar_text) AS ld1_sim',
                                 'n_gram (src_text1, tar_text, 2) AS ngram1_sim',
                                 'jaro_winkler (src_text1, tar_text, 0.1) AS jw1_sim'),
            case.sensitive = TRUE,
            accumulate = c("id","src_text1","tar_text"))
    
    # Print the result.
    print(obj$result)