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---
title: Optimizing Queries on Data Partitioned by a Key or Field Value
---
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You can improve query performance on data that is partitioned by key or a field value by creating a key index and then executing the query using the `FunctionService` with the key or field value used as filter.
The following is an example how to optimize a query that will be run on data partitioned by region key value. In the following example, data is partitioned by the "orderId" field.
1. Create a key index on the orderId field. See [Creating Key Indexes](../query_index/creating_key_indexes.html#concept_09E29507AF0D42CF81D261B030D0B7C8) for more details.
2. Execute the query using the function service with orderId provided as the filter to the function context. For example:
``` pre
/**
* Execute MyFunction for query on data partitioned by orderId key
*
*/
public class TestFunctionQuery {
public static void main(String[] args) {
Set filter = new HashSet();
ResultCollector rcollector = null;
//Filter data based on orderId = '12345'
filter.add(12345);
//Query to get all orders that match ID 12345 and amount > 1000
String qStr = "SELECT * FROM /Orders WHERE orderId = '12345' AND amount > 1000";
try {
Function func = new MyFunction("testFunction");
Region region = CacheFactory.getAnyInstance().getRegion("myPartitionRegion");
//Function will be routed to one node containing the bucket
//for ID=1 and query will execute on that bucket.
rcollector = FunctionService
.onRegion(region)
.setArguments(qStr)
.withFilter(filter)
.execute(func);
Object result = rcollector.getResult();
//Results from one or multiple nodes.
ArrayList resultList = (ArrayList)result;
List queryResults = new ArrayList();
if (resultList.size()!=0) {
for (Object obj: resultList) {
if (obj != null) {
queryResults.addAll((ArrayList)obj);
}
}
}
printResults(queryResults);
} catch (FunctionException ex) {
getLogger().info(ex);
}
}
}
```