Is there a difference between using search terms and should when querying Elasticsearch - elasticsearch

Question

I am performing a refactor of the code to query an ES index, and I was wondering if there is any difference between the two snippets below:
"bool" : {
"should" : [ {
"terms" : {
"myType" : [ 1 ]
}
}, {
"terms" : {
"myType" : [ 2 ]
}
}, {
"terms" : {
"myType" : [ 4 ]
}
} ]
}
and
"terms" : {
"myType" : [ 1, 2, 4 ]
}

Answer 1

Please check this blog from Elastic discuss page which will answer your question. Coying here for quick referance:
There's a few differences.
The simplest to see is the verbosity - terms queries just list an
array while term queries require more JSON.
terms queries do not score matches based on IDF (the rareness) of
matched terms - the term query does.
term queries can only have up to 1024 values due to Boolean's max
clause count
terms queries can have more terms
By default, Elasticsearch limits the terms query to a maximum of
65,536 terms. You can change this limit using the
index.max_terms_count setting.
Which of them is going to be faster? Is speed also related to the
number of terms?
It depends. They execute differently. term queries do more expensive scoring but does so lazily. They may "skip" over docs during execution because other more selective criteria may advance the stream of matching docs considered.
The terms queries doesn't do expensive scoring but is more eager and creates the equivalent of a single bitset with a one or zero for every doc by ORing all the potential matching docs up front. Many terms can share the same bitset which is what provides the scalability in term numbers.