I am trying to use elasticsearch in order to find documents with a rule based on two doc properties.
Lets say the documents are in the following structure:
{
"customer_payment_timestamp" : 14387930787,
"customer_delivery_timestamp" : 14387230787,
}
and i would like to query these kind of documents and find all documents where customer_payment_timestamp is greater than customer_delivery_timestamp.
Tried the official documentation, but I couldn't find any relevant example regarding the query itself or a pre-mapped field... is it even possible?
You can achieve this with a script filter like this:
POST index/_search
{
"query": {
"bool": {
"filter": {
"script": {
"script": "doc.customer_payment_timestamp.value > doc. customer_delivery_timestamp.value"
}
}
}
}
}
Note: you need to make sure that dynamic scripting is enabled
Related
I'm trying to create a query to filter my documents by one (can be anyone) value from a field (in my case "host.name"). The point is that I don't know previously the unique values of this field. I need found these and choose one to be used in the query.
I had tried the below query using a painless script, but I have not been able to achieve the goal.
{
"sort" : [{"#timestamp": "desc"}, {"host.name": "asc"}],
"query": {
"bool": {
"filter": {
"script": {
"script": {
"source": """
String k = doc['host.name'][0];
return doc['host.name'].value == k;
""",
"lang": "painless"
}
}
}
}
}
I'll appreciate if any can help me improving this idea of suggesting me a new one.
TL;DR you can't.
The script query context operates on one document at a time and so you won't have access to the other docs' field values. You can either use a scripted_metric aggregation which does allow iterating through all docs but it's just that -- an aggregation -- and not a query.
I'd suggest to first run a simple terms agg to figure out what values you're working with and then build your queries accordingly.
I want to get all docs that have 10 or more fields in them. I'm guessing something like this:
{
"query": {
"range": {
"fields": {
"gt": 1000
}
}
}
}
What you can do is to run a script query like this
{
"query": {
"script": {
"script": {
"source": "params._source.size() >= 10"
}
}
}
}
However, be advised that depending on the number of documents you have and the hardware that supports your cluster, this can negatively impact the performance of your cluster.
A better idea would be to add another integer field that contains the number of fields that the document contains, so you can simply run a range query on it, like in your question.
As Per Documentation of _source field, you can do this like that or can't get results based on fields count.
https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-source-field.html
I have a question about the Elasticsearch DSL.
I would like to do a full text search, but scope the searchable records to a specific array of database ids.
In SQL world, it would be the functional equivalent of WHERE id IN(1, 2, 3, 4).
I've been researching, but I find the Elasticsearch query DSL documentation a little cryptic and devoid of useful examples. Can anyone point me in the right direction?
Here is an example query which might work for you. This assumes that the _all field is enabled on your index (which is the default). It will do a full text search across all the fields in your index. Additionally, with the added ids filter, the query will exclude any document whose id is not in the given array.
{
"bool": {
"must": {
"match": {
"_all": "your search text"
}
},
"filter": {
"ids": {
"values": ["1","2","3","4"]
}
}
}
}
Hope this helps!
As discussed by Ali Beyad, ids field in the query can do that for you. Just to complement his answer, I am giving an working example. In case anyone in the future needs it.
GET index_name/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"field": "your query"
}
},
{
"ids" : {
"values" : ["0aRM6ngBFlDmSSLpu_J4", "0qRM6ngBFlDmSSLpu_J4"]
}
}
]
}
}
}
You can create a bool query that contains an Ids query in a MUST clause:
https://www.elastic.co/guide/en/elasticsearch/reference/2.0/query-dsl-ids-query.html
By using a MUST clause in a bool query, your search will be further limited by the Ids you specify. I'm assuming here by Ids you mean the _id value for your documents.
According to es doc, you can
Returns documents based on their IDs.
GET /_search
{
"query": {
"ids" : {
"values" : ["1", "4", "100"]
}
}
}
With elasticaBundle symfony 5.2
$query = new Query();
$IdsQuery = new Query\Ids();
$IdsQuery->setIds($id);
$query->setQuery($IdsQuery);
$this->finder->find($query, $limit);
You have two options.
The ids query:
GET index/_search
{
"query": {
"ids": {
"values": ["1, 2, 3"]
}
}
}
or
The terms query:
GET index/_search
{
"query": {
"terms": {
"yourNonPrimaryIdField": ["1", "2","3"]
}
}
}
The ids query targets the document's internal _id field (= the primary ID). But it often happens that documents contain secondary (and more) IDs which you'd target thru the terms query.
Note that if your secondary IDs contain uppercase chars and you don't set their field's mapping to keyword, they'll be normalized (and lowercased) and the terms query will appear broken because it only works with exact matches. More on this here: Only getting results when elasticsearch is case sensitive
I am playing with filters in elasticsearch (we use old version 1.3.1), and I need to filter my search results by any field. With query, this can be done like this:
"query": {
"query_string": {
"query": "_all:test"
}
}
But filters seems to not work with _all statement. What can I do? Would newer elasticsearch version solve my problem?
Thanks in advance!
PS: I need to search exact values, so I cannot use queries. There is difference between queries and filters - if you search for my brown, then you can expect results like:
my brown
This is my brown dog.
someone stolen my brown wallet
But filter will return only my brown, and that is what I need.
You might want to read up a little on the distinction between queries and filters. What you're doing there is a query string query.
If you do actually want to filter against exact text tokens (read up on analysis if you don't know what I mean by "tokens"), AND you have your mapping set up such that the "_all" field behaves as you're expecting then try something like this:
POST /test_index/_search
{
"query": {
"filtered": {
"filter": {
"term": {
"_all": "test"
}
}
}
}
}
If, on the other hand, you want to allow some analysis (so that "Test" is tokenized to "test", for example), you may want this instead:
POST /test_index/_search
{
"query": {
"match": {
"_all": "Test"
}
}
}
Here is some code I used to play around with it:
http://sense.qbox.io/gist/44adf2c2ade8abd6758f0e08ed2e40434850fc1c
This query is returning fine only one item "steve_jobs".
{
"query": {
"constant_score": {
"filter": {
"term": {
"name":"steve_jobs"
}
}
}
}
}
So, now I want to get all people with name prefix steve_. So I try this:
{
"query": {
"constant_score": {
"filter": {
"term": {
"name": "steve_"
}
}
}
}
}
This is returning nothing. Why?
I'm confused about when to use term query / term filter / terms filter / querystring query.
What you need is Prefix Query.
If you are indexing your document like so:
POST /testing_nested_query/class/
{
"name": "my name is steve_jobs"
}
And you are using the default analyzer, then the problem is that the term steve_jobs will be indexed as one term. So your Term Query will never be able to find any docs matching the term steve as there is no term like in the index. Prefix Query helps you solve your problem by searching for a prefix in all the indexed terms.
You can solve the same problem by making your custom analyzers (read this and this) so that steve_jobs is stored as steve and jobs.