Hi, looking for your recommendations on the best way to do approximate text search in the Data service.
For simplicity, suppose a Data table with one string member that can be multi-word strings. We assume users are can mispell words and may not specify in a query in the same order they occur in the target string in the data table column.
One might use something like Lucene to do this kind of approxmate matching. Presumably one would have run a Lucene server that first matches a query string to a string (or strings) that occurs in the Data service table and using that result to actually query Backendless. It doesn’t appear one could run a Lucene instance on Backendless itself.
The Backendless Data service docs say that Backendless essentially implements the SQL-92 WHERE clause where the “LIKE” predicate is probably the only relevant approximate string matching predicate. Assuming “LIKE” is available, one might propose two general solutions as a half-way step in which one isn’t concerned with word order, only a general class of per-word misspellings:
One could reduce a query string to a pattern string and try to match to that.
One could create a column of stemmed strings in Backendless and reduce the user’s query string to a stemmed string, and then perhaps to a pattern string, and match to that.
Any suggestions for a better, more flexible solution?