August 17, 2023

tSynonymSearch – Docs for ESB 5.x

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tSynonymSearch

tSynonymSearch_icon32_white.png

Warning

This component will be available in the Palette of
Talend Studio on the condition that you have subscribed to one of
the Talend Platform products.

tSynonymSearch Properties

Component family

Data Quality

  

Function

tSynonymSearch reads input data
and searches for reference entries defined in a given synonym index.
If this component finds matched entries in the synonym index, it
outputs them along with the corresponding input data and the
relative matching details.

For further information about how to create a synonym index and
define the reference entries, see tSynonymOutput.

For further information about how to access and manage the words
and the reference entries (documents) of an existing synonym index
using the synonym index editor, see the Talend Studio User Guide.

For further information about available synonym indexes, see the
appendix about data synonym dictionaries in the Talend Studio User Guide.

Note

The synonym similarity computation is enhanced since the
Studio version 5.1. If your indexes were created with version
5.0 or lower and you need to handle them using this enhanced
computation method, you have to update these indexes by
executing the IndexMigrator.jar file downloadable from: http://talendforge.org/svn/top/trunk/org.talend.dataquality.standardization.migration/dist/IndexMigrator.jar.
The command to be used to run this jar file is

Purpose

tSynonymSearch searches a given
index for the reference entries matching the data you input.

Basic settings

Schema and Edit
schema

A schema is a row description, it defines the number of fields to be processed and
passed on to the next component. The schema is either Built-in or stored remotely in the
Repository.

Since version 5.6, both the Built-In mode and the Repository mode are
available in any of the Talend solutions.

Default columns are provided in the schema of this component in
order to present the matching details between the input data and the
reference entries.

For further information about the default schema columns, see
Default schema columns

 

 

Built-in: The schema will be
created and stored locally for this component only. Related topic:
see Talend Studio User Guide.

 

 

Repository: The schema already
exists and is stored in the Repository, hence can be reused in
various projects and job designs. Related topic: see
Talend Studio User
Guide.

 

Limit of each group

Type in a number to indicate the maximum display of the reference
entries matched to each group of the input data. Each row of input
data is recognized as one group by this component.

If the entries count exceeds the indicated limit, this component
displays the ones scored the highest. For further information about
the scores used on the matched entries, see Default schema columns.

 

Columns to search

Complete this table to provide parameters used to match the input
data and the reference entries in a given index.

The columns to be completed are:

– Input column: select the
column(s) of interest from the input data schema.

– Reference output column:
select the column(s) from the output data schema to present the
matched reference entries found in the given synonym index.

– Index path: enter, in
quotation marks, the path to the index you need to search.

– Search mode: select the search
mode you want to use to match input strings against index strings.
For further information about available search modes, see Search modes for Index rules.

– Score threshold (available for
all modes): set a numerical value above 0.0 by
which you want to filter the results. Set the threshold to
0.0 to disable the filter.

The score value is returned by the Lucene engine and can be
anything above 0. The higher the score is, the
higher is the similarity of the match. Use the threshold to remove
low scoring matches from the output results. There is no easy way to
decide about a good threshold value. It will depend on the input
data and the indexed data.

– Min similarity (based on the
Levenshtein algorithm and available for the Match all
fuzzy and Match any fuzzy
modes): set the minimum similarities requested in a token to match
an index string. The value is between 0 and
1, default value is 0.8. When the value is
closer to 1, only terms with higher similarity will be
matched.

– Word distance (available for
the Match partial mode): select from the list
the maximum number of words allowed to come inside a sequence of
words that may be found in the index, default value is
1.

– Limit: type in a number to
indicate the maximum reference entries to be matched to each record
of the corresponding input column you have selected.

Advanced settings

tStatCatcher Statistics

Select this check box to collect log data at the Job and the
component levels.

Connections

Outgoing links (from this component to another):

Row: Main; Reject

Trigger: Run if; On Component Ok;
On Component Error.

Incoming links (from one component to this one):

Row: Main; Reject

For further information regarding connections, see
Talend Studio User
Guide.

Global Variables

ERROR_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error check box is
cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space to access the variable list and choose the variable to use from it.

For further information about variables, see Talend Studio
User Guide.

Usage

This component needs incoming data from the preceding
component.

Default schema columns

This section presents the detailed information about the default schema columns
provided natively with the tSynonymSearch
component.

Columns

Description

GID

Group IDs. These IDs are created automatically at runtime to
index the input data groups recognized by this component.

GRP_SIZE

Numbers of the matched reference entries for each group of the
input data. This size is limited by the number you set in the
Limit of each group field
and presents always the entries scored the highest.

SCORE

Lucene score used to measure in total the match degree between
the selected input columns and their matched reference entries.
The Lucene score is a numerical value that starts from
0 and is not bounded. Good matches
will usually score higher than 1, but there
is no definite rule to choose what is a good match and what is a
bad match.

SCORES

Lucene scores used to measure the match degree between each
input column you have selected and its matching reference
entries.

NB_MATCHED _FIELDS

Number of the input columns you have selected for the matching
operation.

In addition to the matching-related information presented in the default schema
columns, you need to define more columns in order to output the input data and their
matched reference entries.

 

Scenario 1: Searching a given index for matched reference entries

In this scenario, a three-component Job reads the provided first name data, searches a
given synonym index for reference entries that match the input data and then outputs the
results.

Create a first-name synonym index for this Job following the procedures outlined in
Scenario 2: Creating a synonym index for people names using tMap.

The three components used in this Job are:

  • tFixedFlowInput: this component generates the
    input data you will match against the reference entries in the synonym
    index.

  • tSynonymSearch: this component searches for
    the matched reference entries in the synonym index.

  • tLogRow (found): this
    component lists the result of this matching search.

Use_Case_tSynonymSearch2.png

Setting up the Job

  1. Drop tFixedFlowInput, tSynonymSearch and tLogRow from the Palette
    onto the design workspace.

    You can change the displayed name of each of these component as what has
    been done for the tLogRow component, named
    found in this scenario. For further information,
    see Talend Studio User Guide.

  2. Right-click the tFixedFlowInput component
    to open the contextual menu and select Row > Main.

  3. Drop the link on the tSynonymSearch
    component to create an connection between these two components.

  4. Do the same thing to connect tSynonymOutput to tLogRow
    (found).

Configuring the components

  1. Double-click tFixedFlowInput to open its
    Basic settings view.

    Use_Case_tSynonymSearch3.png

  2. Next to the Schema field, click the
    Edit schema button to open the
    [Schema] dialog box, add one column and
    name it FIRSTNAME. When done, click OK to validate these changes and close the dialog
    box.

    Use_Case_tSynonymSearch4.png

  3. In the Mode area, select the Use Inline Content (delimited file) option, and
    supply the following names in the Content
    field:

  4. Double-click tSynonymSearch to open its
    Basic settings view.

    Use_Case_tSynonymSearch5.png

  5. Click Sync columns to add the schema
    columns of its preceding component to the default schema columns of
    tSynonymSearch.

    When prompted, click Yes to propagate the
    changes to the next component.

  6. Click the […] button next to Edit schema to open the [Schema] dialog box, and add one column to the output
    schema: matched_fname.

    This column will hold the matched reference entries in the output
    flow.

    When done, click OK to validate the
    setting and accept propagating the changes when prompted.

    Use_Case_tSynonymSearch6.png

  7. In the Limit of each group field, type in
    5 to replace the default value.

  8. Under the Columns to search table, click
    the [+] button to add one row and define
    the parameters as follows:

    • In the Input column column,
      select FIRSTNAME from the list of the input
      columns.

    • In the Reference output column
      column, select matched_fname from the list of
      the output columns.

    • In the Index path column, type in
      the path to the synonym index to be used, between double quotation
      marks.

    • In the Search mode column, select
      Match all fuzzy. This will match each word
      of the input string against similar word of the index string.

    • In the Score threshold column,
      enter 0.9 to filter results and list only terms
      with higher similarity.

    • In the Min similarity column,
      keep the default value 0.8 as the minimum
      similarities requested in a token to match an index string. When the
      value is closer to 1, only terms with higher similarity will be
      matched.

    • Leave the Word distance column as
      it is only for the Match partial mode.

    • In the Limit column, leave the
      default value 5.

  9. In the Basic settings view of the
    tLogRow component, select the Table option for better readable display of the
    Job execution result.

Executing the Job

  • Press F6 to run this Job.

    The execution result reads as follows in the console of the Run view.

    Use_Case_tSynonymSearch7.png

    From this result, you can see that each first name of the input string
    matches a similar word of the index string. For example, the entry Chris from the input flow is found to fuzzy
    match 5 words in the given synonym index. And this
    record is recognized as group 2 that has a group size
    equal to 5, meaning that five matched reference entries
    are found for this group.

    The SCORE and the SCORES columns
    present the same values in this scenario because only one input column is
    used.

    If you want to extract only the input entries that match exactly an index
    string, select Match exact in the Search mode column in tSynonymSearch basic settings.

Scenario 2: Searching for matched reference entries for two input columns

In this scenario, you are going to use the previous Job with slight modifications on
it in order to search two synonym indexes for input data from two columns.

In addition to the index used earlier, another index is used alongside holding the
last name data, for example, Correia, Corria,
Toum, Toom, toom,
Walker, Waker.

To replicate this scenario, open the Job created in the previous section and proceed
as follows:

Configuring the components

  1. Double-click tFixedFlowInput to open its
    Basic settings view.

    Use_Case_tSynonymSearch_1.png

  2. Next to Edit schema, click the […] button to open the [Schema] dialog box, and add a second column
    LASTNAME next to the FIRSTNAME
    column you have defined in the previous scenario.

    When done, click OK to validate this
    change and thus close the dialog box.

    Use_Case_tSynonymSearch_2.png

  3. In the Content field of the Mode area, add more first name and last name data
    to make the input data read as
    follows:

  4. Double-click tSynonymSearch to open its
    Basic settings view.

    Use_Case_tSynonymSearch_4.png

  5. Click Sync columns to synchronize the
    columns of this component with the preceding one and click Yes to propagate the changes to the next
    component when prompted.

  6. Click the […] button next to Edit schema to open the [Schema] dialog box, and add two columns to the output
    schema: matched_fname and
    matched_lname.

    These columns will hold the matched reference entries in the output
    flow.

    When done, click OK to validate the
    setting and accept propagating the changes when prompted.

  7. In the Limit of each group field, type in
    10 to replace the one you have defined in the
    previous scenario.

  8. Under the Columns to search table, click
    the [+] button to add a second row and
    define the parameters as follows:

    • In the Input column column,
      select LASTNAME from the drop-down list.

    • In the Reference output column
      column, select matched_lname from the drop-down
      list.

    • In the Index path column, type
      in, between quotation marks, the path to the synonym index holding
      the last name entries.

    • In the Search mode column, select
      Match exact for both input columns. This
      will match the exact input word against an exact index word.

    • In the Score threshold column,
      enter 0.9 to filter results and list only terms
      with higher similarity.

    • Leave the Min similarity and
      Word distance columns as they
      are only for the fuzzy modes and the Match
      partial       mode respectively.

    • In the Limit column of this row,
      leave the default value 5.

Executing the Job

  • Press F6 to run this Job.

    The execution result reads as follows in the console of the Run view.

    Use_Case_tSynonymSearch_5.png

    From this result, if you take the input data Chris
    Toom     for example, you can see that:

  • this record is recognized as group 2 with a group size equal to 3. This
    means that 3 pairs of exact match reference entries are found from the two
    synonym indexes in use. The exact match for the first name are
    Christian, Christiaan and
    Christoffel, and the exact match for the last name
    are toomx3.

  • the SCORES column contains two sub-columns.

    These sub-columns present the matching scores in regards to the
    matched_fname and to the
    matched_lname reference columns respectively. Each
    figure listed in the SCORE column is equal to the sum
    of the two figures of the same row in the sub-columns of the
    SCORES column.

Document get from Talend https://help.talend.com
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