Given the following model structure:
{
"trans": {
"cust": {
"firstname": "Bone",
"lastname": "Klebes",
"email": "[hidden email]",
"gender": "Male"
},
"ipaddress": "104.89.149.184",
"date": "2017-12-01",
"amount": 1217,
"currency": "NOK"
}
}
What is the recommended storage strategy for optimum querying?
(example: date='2018-12-01' and lastname='Klebes' and amount > 1000)
I have tried the following strategies on a partitioned, two-node cluster
having 1 000 000 documents, with the following results:
1. - DataGrid:
One document per record
Using IgniteBiPredicate in ScanQuery
Time taken: ~1.5 sec
Inserts are quite fast (1 000 000 documents = 1 000 000 records = 35
min)
2. - SQL:
Table structure - [id(PK)], [doc_id], [key], [val] (all columns
indexed)
One record for each field (8 records per document)
Using nested JDBC JOIN query
Time taken: ~20ms (PostgreSQL comparison = ~10ms)
Inserts are very slow (1 000 000 documents = 8 000 000 records = 10
hours)
Is there another strategy that I should consider? Or any techniques that I
can use to optimise the queries?
Thanks.
--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/
