I'm using Spring-Data's Query Creation as described here.
I have an ID to Person, and also a secId which is also a unique Id.
I want to be able to write
Person findBySecId(long secId);
Because I know that I will get only one result.
Right now as I've seen, I can only write
List<Person> findBySecId(long secId);
and then I have to extract the first element.
Is there any known way to do what I want?
Related
I'm using Solr to run a query on one of our cores. Suppose my documents have two fields: ID, and Name. I also have a separate list of IDs I'm grabbing from a database and passing into the query to boost certain results.
If the document gets returned in the query and the ID is in the list it goes to the top of the results, and if it gets returned in the query and the ID is not in the list then it goes below those that are in the list. The former is from the "boost". My query is something like this -
http://mysolrserver:8983/solr/MyCore/MyQueryHandler?q=Smith&start=0&rows=25&bq=Id%3a(36+OR+76+OR+90+OR+224+OR+391)
I am able to get the boost query working but I need the boosted results to be in alphabetical order by name, then the non boosted results under that also in alphabetical order by name. I need to know what to user for the &sort= parameter.
&sort=score%20desc,Name+asc does not work.
I've looked over a lot of documentation, but I still don't know if this even possible. Any help is appreciated. Thanks!
Solr version is 6.0.1. I am actually using SolrNet to interface with Solr, but I think I can figure out the SolrNet part if I know what the url's &sort= parameter value needs to be.
I figured it out, by doing away with the boost query. I added a sort query using the "exists" function and passing it a sub-query for the ID. The exists returns a boolean value to sort on, then I added the name as a second sort. It works perfect!!
The URL looks like this:
http://mysolrserver:8983/solr/MyCore/MyQueryHandler?q=Smith&start=0&rows=25&sort=exists(query({!v=%27Id:(36+OR+76+OR+90+OR+224+OR+391)%27}))%20DESC,%20Name%20ASC
The closest match to your requirement is the query elevation component[1] .
In your particular case I would first sort my Ids according to my requirements ( sorting them by name for example), then maintain them in the elevate.xml.
At query time you can use the "forceElevation" parameter to force the elevation and then sort the remaining results by name.
[1] https://cwiki.apache.org/confluence/display/solr/The+Query+Elevation+Component
We have a simple web page, where the user can provide some input and query the database. We currently use mongodb but want to migrate to elasticsearch, since the queries are faster.
There are some required search fields, like start and end date, and some optional ones, like a search string to match an entry, or a parent search string, to match parent entries. Parent-child relations are just described through fields containing each entry's ancestors ids.
The question is the following: If both search and parent search string are provided, is there a way to know before executing the queries, which query should be executed first, in order to provide results faster and to be more performant?
For example, it could be that a specific parent search results in only 2 docs/parent entries, and then we can fetch all children matching the search string. In that case we should execute firstly the parent query and then the entry query.
One option would be to get the count of both queries and then execute first the one with the smallest count, but isn't this solution worse, since the queries are going to be executed twice? Once for the count and once for the actual query.
Are there any other options to solve this?
PS. We use elasticsearch v1.7
Example
Let's say the user wants to search for all entries matching the following fields.
searchString: type:BLOCK AND name:test
parentSearchString: name:parentTest AND NOT type:BLOCK
This means that we either have to
fetch all entries (parents) matching the parentSearchString and store their ids. Then, we have to fetch all entries that match the searchString and also have to contain any of the parent ids in the ancestors field.
OR
fetch all entries that match the searchString and store all ancestors ids. Then fetch all entries that match the parentSearchString and their id is one of the ancestors ids.
Just to clarify, both parent and children entries have the exact same structure and reside in the same index. We cannot have different indices since the pare-child relation can be 10 times nested, so an entry can be both a parent and a child. An entry looks more or less like:
{
id: "e32452365321",
name: "name",
type: "type",
ancestors: "id1 id2 id3" // stored in node as an array of ids
}
First of all, I would advise you, to upgrade your Elasticsearch version, if possible. There happened a lot since 1.7 and to be honest, I can't tell if all of what's written in the following article is valid for such an old version (probably it isn't).
But to your actual question: Hopefully I am understanding you correctly, but you try to estimate how costly a query for Elasticsearch is? Well, you don't have to. If you provide all 'queries' in one nested query, Elasticsearch will do that for you: https://www.elastic.co/blog/elasticsearch-query-execution-order
Regarding speed, there is one other thing I can mention: calculating score does take time. So if sorting is not based on the elasticsearch _score, you want to use boolean filter queries. This would also apply, if you want to sort only by _score of parent matches, then you could put the query for children into a filter.
update
Thanks to your example, I now see the problem. Self referencial Parent-Child relations are unfortunately not supported by ElasticSearch, so your approach is probably right. You might want to check out the short chapter of the documentation about application-joins.
So yes, in general, you want to send the second query with the least possible amount of ids/terms. While getting counts for both queries is not as bad as you might think, because the results are most likely still cached, does it actually help? Because if you're going from child to parent, you would have to count the ancestors (field values), and not the actual document count.
I would argue, that the most expensive operation is very often fetching result source from disk. So whichever way you go, you probably should only fetch what you need in the first query. So your options are:
Fetch only the id of parent matches, and then use a terms filter on ancestors in the second query.
Or, fetch only the ancestors field of child matches, and use an id filter in your second query.
Unfortunately, I can't help you more than that, since I don't have enough experience in comparing speed of those approaches. My guess would be, that an id filter might be faster in general. But that's just a guess...
Based on FHIR spec, I know I can do a search on patients and ask that all RiskAssessments be included for each patient (using _revinclude) -- but what if I'm interested only in the most recent RiskAssessment? Or better yet, the most recent RiskAssessment for a specific RiskAssessment.method. Is there a way to accomplish this with a single query?
You could query on RiskAssessment and do a forward include of Patient. If you do that, you can then filter on method. (And via chaining, also filter on what patients to include). There's no way to do "most recent" and get back multiple patients. (For a single patient, sort by descending date and restrict to only 1 instance). However, you could define your own search parameter to assert that filter. (You can also submit a change request to propose such a parameter be defined in general - I'd recommend making the parameter an integer so that you can retrieve the N most recent.)
Im trying filter records with that has a specific value key and delete them. I tried "withFields" and "hasFields" but seems that i can't apply delete to them. My question is how can i do that?
r.db('databaseFoo').table('checkpoints').filter(function (user) {
return user('type').default(false);
}).delete();
If you want all documents that have a type key, you can use hasFields for that.
r.db('databaseFoo').table('checkpoints')
.hasFields('type')
In your current query, what you are doing is getting all documents that don't have a type key or where the value for type is equal to false. This might be what you want, but it's a little confusing if you only want documents that have a type property.
Keeping a reference to the original document
The problem with using hasFields is that it converts a selection (a sequence with a reference to the specific rows in the database) that you can update, and delete into a sequence, with which you can't do that. This is a known issue in RethinkDB. You can read this blog post to understand the different types in ReQL a bit better.
In order to get around this, you can use the hasFields method with the filter method.
r.db('databaseFoo').table('checkpoints')
.filter(r.row.hasFields('type'))
.delete()
This query will work since it returns a selection which can then be passed into delete.
If you want to get all records with with a specific value at a specific key, you can do so a couple of different ways. To get all documents where the property type is equal to false, you can do as follows:
r.db('databaseFoo').table('checkpoints')
.filter({ type: false })
or, you can do:
r.db('databaseFoo').table('checkpoints')
.filter(r.row('type').eq(false))
I'm trying to do the following: I want to create a set of candidates by querying each field separately and then adding the top k matches to this set. After I'm done with that, I need to run another query on this candidate set.
The way how I implemented it right now is using a QueryWrapperFilter with a BooleanQuery that matches the unique id field of each candidate document. However, this means I have to call IndexSearcher.doc().get("docId") for each candidate document before I can add it to my BooleanQuery, which is the major bottleneck. I'm only loading the docId field via MapFieldSelector("docId).
I wanted to create my own Filter class, but I can't use the internal Lucene doc ids directly, because they are specified per segment. Any thoughts on how to approach this?
Instead of reading the stored docId, index the field (it probably already is) and use the FieldCache to retrieve docIds much faster. Then instead of using the docIds in a BooleanQuery, try using a TermsFilter or FieldCacheTermsFilter. The latter documentation describes the performance trade-offs.