How am I able to put both of these queries together, as you can see that query one is bringing back all the date from today and the second query is bringing back data for all users that has the name test in it.
So I want to bring back all of the data for data with the name that has test in it.
Could someone show me how this is done please?
Query one:
{
"_source":["VT"],
"query": {
"range": {
"VT": {
"gte": "now/d",
"lt": "now/d+13h"
}
}}
}
Query two:
from elasticsearch import Elasticsearch
es = Elasticsearch(["9200"])
res = es.search(index="search", body=
{
"_source": ["DTDT", "TRDT"],
"query": {
"bool": {
"should": [
{"wildcard": {"N": "TEST*"}}
]
}
}
}, size=10
)
for doc in res['hits']['hits']:
print(doc)
You can use a bool query with two must clauses, like this:
{
"_source": ["DTDT", "TRDT", "VT"],
"query": {
"bool": {
"must": [
{
"range": {
"VT": {
"gte": "now/d",
"lt": "now/d+13h"
}
}
},
{
"wildcard": {
"N": "TEST*"
}
}
]
}
}
}
Check out the docs for the bool query.
This will help you:
POST _search
{
"query": {
"bool": {
"must": [
{
"range": {
"VT": {
"gte": "now/d",
"lt": "now/d+13h"
}
}
},
{
"match": {
"N": {
"query": "TEST",
"operator": "and"
}
}
}]
}
}
}
Related
My current elasticsearch query is-
{
"must": [
{
"range": {
"firstClosedAt": {
"gte": 1667948400000,
"lte": 1668034800000
}
}
},
{
"term": {
"status": "CLOSED"
}
}
I want to modify it such that if "firstClosedAt" is null or not present then look for "closedAt".
Just like we have coalesce("firstClosedAt","closedAt") in sql
Help would be appreciated
There's no coalesce equivalent in ES, but you can do the query like below, which can read like: "either use firstClosedAt OR use closedAt if firstClosedAt does not exist":
{
"query": {
"bool": {
"filter": [
{
"term": {
"status": "CLOSED"
}
},
{
"bool": {
"minimum_should_match": 1,
"should": [
{
"range": {
"firstClosedAt": {
"gte": 1667948400000,
"lte": 1668034800000
}
}
},
{
"bool": {
"must_not": {
"exists": {
"field": "firstClosedAt"
}
},
"filter": {
"range": {
"closedAt": {
"gte": 1667948400000,
"lte": 1668034800000
}
}
}
}
}
]
}
}
]
}
}
}
You could, however, create a much simpler query if you create another date field at indexing time which would either take the value of firstClosedAt or closedAt if firstClosedAt does not exist
Query: Get employee name "Mahesh" whose id is "200" and joining datetime is in a given date range and his epf status must be either 'NOK' or 'WRN'. (Possible values of epf_status are {OK,NOK,WRN,CANCELLED}.
I have written the following query, that matches epf_status also with OK, CANCELLED, but it must only match when epf_status is either 'NOK' or 'WRN'. What else do I need to change to make it work, as required?
GET myindex01/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"empname": { "query": "Mahesh", "operator": "AND" }
}
},
{
"match": {
"empid": { "query": "200", "operator": "AND" }
}
},
{
"range": {
"joining_datetime": {
"gte": "2020-01-01T00:00:00",
"lte": "2022-06-24T23:59:59"
}
}
}
],
"should": [
{ "match": { "epf_status": "NOK" } },
{ "match": { "epf_status": "WRN" } }
]
}
}
}
SAMPLE DATA:
{"Mahesh","200","2022-04-01","OK"}
{"Mahesh","200","2022-04-01","NOK"}
{"Mahesh","200","2022-04-01","WRN"}
{"Mahesh","200","2022-04-01","CANCELLED"}
REQUIRED OUTPUT:
{"Mahesh","200","2022-04-01","NOK"}
{"Mahesh","200","2022-04-01","WRN"}
Tldr;
You could be using the terms query for that I believe.
Returns documents that contain one or more exact terms in a provided field.
To solve
GET myindex01/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"empname": { "query": "Mahesh", "operator": "AND" }
}
},
{
"match": {
"empid": { "query": "200", "operator": "AND" }
}
},
{
"range": {
"joining_datetime": {
"gte": "2020-01-01T00:00:00",
"lte": "2022-06-24T23:59:59"
}
}
}
],
"should": [
{ "terms": { "epf_status": ["NOK", "WRN"] } }
]
}
}
}
I have this following query with elastic:
{
"query": {
"bool": {
"filter": [{
"terms": {
"participants.group": ["group1","group2"]
}
}, {
"range": {
"recordDate": {
"gte": "2020-05-14 00:00:00.000",
"lte": "2020-07-22 20:30:56.566"
}
}
}]
}
}
}
Currently, this finds records with participants with group "group1" and "group2".
How to change the query so it finds records with participants from "group1" or "group2?
Is it possible to do it without changing the structure of the query?
I'm assuming that the field participants.group is of keyword type and not text type.
Assuming that, the query you have roughly translates to (group1) or (group2) or (group1 and group2).
All you need to do is modify the query as below and add a must_not clause like below:
POST my_filter_index/_search
{
"query": {
"bool": {
"filter": [
{
"bool": {
"must": [
{
"range": {
"recordDate": {
"gte": "2020-05-14 00:00:00.000",
"lte": "2020-07-22 20:30:56.566"
}
}
}
],
"should": [
{
"terms": {
"participants.group": ["group1", "group2"]
}
}
]
}
}
],
"must_not": [
{
"bool": {
"must": [
{
"term": {
"participants.group": "group1"
}
},
{
"term": {
"participants.group": "group2"
}
}
]
}
}
]
}
}
}
Let me know if that works!
I'm looking to get data between two dates in elasticsearch.
I have tried to put "gte": "20-04-2019" and "lte": "21-04-2019" as shown below, but I still get other anterior dates in the final result:
GET aws-index2/produit/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"commun.nom": {
"query": "iphone",
"operator": "and",
"zero_terms_query": "all"
}
}
},
{
"range": {
"commun.date": {
"gte": "20-04-2019",
"lte": "21-04-2019",
"format": "dd-MM-yyyy"
}
}
}
]
}
}
}
In the sample document you give, commun.date looks like this "04-20-2019", which means that the format is not dd-MM-yyyy but MM-dd-yyyy. So your query should probably look like this instead:
GET aws-index2/produit/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"commun.nom": {
"query": "iphone",
"operator": "and",
"zero_terms_query": "all"
}
}
},
{
"range": {
"commun.date": {
"gte": "04-20-2019",
"lte": "04-21-2019"
}
}
}
]
}
}
}
I have 2 types of queries. They are both logically identical however I'm not sure if there is any performance difference between the two.
I will be glad if someone can enlighten me.
Using match_all and filter:
{
"query": {
"filtered": {
"query": {
"term": {
"user_id": "1234567"
}
},
"filter": {
"bool": {
"must": [
{
"range": {
"ephoc_date": {
"lt": 1437033590,
"gte": 1437026390
}
}
}
]
}
}
}
}
}
Using term query:
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"must": [
{
"term": {
"user_id": "1234567"
}
},
{
"range": {
"ephoc_date": {
"lt": 1437033590,
"gte": 1437026390
}
}
}
]
}
}
}
}
}
Looking at your query it seems like you don't care about how documents are scored based on the value of user_id field being "1234567". What I mean to say is - If more than one document have user_id set to "1234567", you don't care about the order of documents in the result. If that is the case, 2nd option is better with respect to performance because there is some computation cost associated with scoring in the 1st query while there is no scoring in the 2nd query. By the way, your 2nd query can also be simplified to below:
{
"filter": {
"bool": {
"must": [
{
"term": {
"user_id": "1234567"
}
},
{
"range": {
"ephoc_date": {
"lt": 1437033590,
"gte": 1437026390
}
}
}
]
}
}
}