This page describes example workflows that demonstrate the usage of the
Table Indexer and
Index Query node of the Indexing & Searching plug-in.
The first example demonstrates an advanced query that filters a given input table based on the values of several columns. The second example explains the indexing and searching of document collections. The third example uses the Indexing & Searching plugin to identify typos in a given address database.
All example flows can be downloaded from the public KNIME server using the KNIME Example Flow Server view. The workflows are located in the 015_IndexingAndSearching section. The corresponding name of each workflow in the repository is written in brackets in the following descriptions.
For a detailed description on how to connect to the public KNIME server and download the example workflows click here.
This workflow demonstrates how to perform an advanced query to search in a data table with 100.000 customers for customer that sattisfy several criteria i.e. their first name should start with A,B or C and they should be between 20 and 40 years old.
This workflow uses severall queries to search in a collection of 1.000 documents. The query nodes demonstrate different query options such as range queries for publication dates and wildcard searches for author names.
This workflow demonstrates the usage of the Indexing & Searching plug-in in order to detect typos in a large address database using fuzzy queries. The flow generates 50% fake addresses using the Data Generation plug-in by random shuffling characters of the different data columns i.e. name, plz, street, etc. It loops over all addresses and searches for fuzzy matches in the indexed address database.