CODEWITHSUNDEEP
elasticsearch
mfeingold
mfeingold

Reputation: 7154

How to write fast Elastic Search queries

Is there a guide to writing the ES queries - what to do, what to avoid, this sort of stuff. The official site describes all various ways to search, but provides little giudance as to when select what.

In my particular instance I have a list of providers, each one has a name an address and a number of IDs. I want to give the user a box he can type in anything he knows about the provider and run search based on whatever is provided. Essentially I would like to match every word from the box against the records (documents) in the index.

For the end user this should look like a simple keyword search.

Matching should cover exact matches, wild card matches, phonetic matches, synonyms (for names). Also some fuzziness should be included too.

The official site describes various ways to do that, but how to combine them together? For instance to support wild card search do I use wild card query, or do I index it with the NGram and do just text query?

With the SQL queries a certain way to get this sort of information is to check the execution plan for the query. If the SQL optimizer tells you that it will use table scan against a table of considerable size, you know you should change your query, or, may be, add an index. AFAIK there is no equivalent for this powerful feature in ES and I am not even sure if it is possible to build it.

But at least some generic considerations...? Pretty please...

Upvotes: 4

Views: 4791

Answers (2)

Venkata Naresh
Venkata Naresh

Reputation: 366

One correction from the above - Filters are cacheable by ES, and not queries. Queries does the extra step of relevance scoring & full text search. So, where ever full text search is not needed using filter is advised.

Also, design your mappings with correct index values (not_analyzed, no, analyzed)

Upvotes: 0

Jonathan Moo
Jonathan Moo

Reputation: 3267

There is not a best way to go about doing things, because a lot of times it depends on what you are indexing, and how you map your data into variables within Elasticsearch.

Some rule of thumb that you should look out for:

a. Faceted Queries in Elasticsearch work in sequences:

{   
 "query": {
   // data will be searched from this block first //
 }, "facets": {
   // after the data is received, it will be processed into facets //
 }
}

Hence if your query size is huge, you are going to slow down your query further by faceting. Monitor the results of your query.

b. Filters vs Queries

Filters do a subset of your queries, meaning it will take the entire result of what your query is, and then filter out what you do want or what you do not want.

Queries are usually direct searches for data.

Hence, if you can make your query as specific as possible before you do a filter, it should yield faster results.

c. Queries are cached; running them again and again will generally yield faster responses. The Warmers API should be able to make your queries even quicker if you are always going to use the same set of queries

Again, all these are rule of thumbs and cannot be followed strictly, because what you index into specific variables will affect processing times. A string is different from long types, and strings with analyzers are different from non-analyzers. What you need to do is probably to experiment with your queries to get a better judgement.

Upvotes: 2

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