OR is spelled should AND is spelled must NOR is spelled should_not Example: You want to see all the items that are (round AND (red OR blue)): { “query”: { “bool”: { “must”: [ { “term”: {“shape”: “round”} }, { “bool”: { “should”: [ {“term”: {“color”: “red”}}, {“term”: {“color”: “blue”} ] } } ] } … Read more
The filtered query has been deprecated and removed in ES 5.0. You should now use the bool/must/filter query instead. { “query”: { “bool”: { “must”: { “multi_match”: { “operator”: “and”, “fields”: [ “author”, “title”, “publisher”, “year” ], “query”: “George Orwell” } }, “filter”: { “terms”: { “year”: [ 1980, 1981 ] } } } } … Read more
I’ll try to explain with a real example since the answer and replies you got don’t seem to help you. When you download elasticsearch and start it up, you create an elasticsearch node which tries to join an existing cluster if available or creates a new one. Let’s say you created your own new cluster … Read more
I’m using nGram, too. I use standard tokenizer and nGram just as a filter. Here is my setup: { “index”: { “index”: “my_idx”, “type”: “my_type”, “analysis”: { “index_analyzer”: { “my_index_analyzer”: { “type”: “custom”, “tokenizer”: “standard”, “filter”: [ “lowercase”, “mynGram” ] } }, “search_analyzer”: { “my_search_analyzer”: { “type”: “custom”, “tokenizer”: “standard”, “filter”: [ “standard”, “lowercase”, “mynGram” … Read more
You’ve pretty much listed the two main options there are when it comes to search across multiple data stores, i.e. search in one central data store (option #1) or search in all data stores and aggregate the results (option #2). Both options would work, although option #2 has two main drawbacks: It will require a … Read more