kgyrtkirk commented on code in PR #16660:
URL: https://github.com/apache/druid/pull/16660#discussion_r1673549858
##########
docs/querying/sql.md:
##########
@@ -409,3 +409,26 @@ To solve this issue, explicitly provide the type of the
dynamic parameter using
```
SELECT * FROM druid.foo WHERE dim1 like CONCAT('%', CAST (? AS VARCHAR), '%')
```
+
+Dynamic parameters can also replace arrays, reducing the parsing time.
+
+for example:
+```json
+{
+ "query": "SELECT doubleArrayColumn from druid.table where
ARRAY_CONTAINS(?, doubleArrayColumn)",
+ "parameters": [
+ {"type":"ARRAY", "value":[-25.7, null, 36.85]}
+ ]
+}
+```
Review Comment:
I feel like this is `sql-api` specific so it shouldn't it be inside
`../api-reference/sql-api.md` ?
##########
docs/querying/sql.md:
##########
@@ -409,3 +409,26 @@ To solve this issue, explicitly provide the type of the
dynamic parameter using
```
SELECT * FROM druid.foo WHERE dim1 like CONCAT('%', CAST (? AS VARCHAR), '%')
```
+
+Dynamic parameters can also replace arrays, reducing the parsing time.
+
+for example:
+```json
+{
+ "query": "SELECT doubleArrayColumn from druid.table where
ARRAY_CONTAINS(?, doubleArrayColumn)",
+ "parameters": [
+ {"type":"ARRAY", "value":[-25.7, null, 36.85]}
+ ]
+}
+```
+
+Also, an IN filter being supplied with a lot of values, can be replaced by a
dynamic parameter passed inside
[SCALAR_IN_ARRAY](sql-functions.md#scalar_in_array)
+```json
+{
+ "query": "SELECT count(city) from druid.table where SCALAR_IN_ARRAY(city,
?)",
+ "parameters": [
+ {"type":"ARRAY", "value":["Vienna", "Seoul", "San Francisco"]}
+ ]
+}
+```
Review Comment:
I've played with similar things for jdbc api earlier; it seemed a bit harder
to use it from there
should we include those in `sql-api.md`?
```java
import com.google.common.base.Joiner;
import com.google.common.collect.ImmutableList;
import org.apache.calcite.avatica.ColumnMetaData;
import org.apache.calcite.avatica.SqlType;
import org.apache.calcite.avatica.ColumnMetaData.AvaticaType;
import org.apache.calcite.avatica.ColumnMetaData.Rep;
import org.apache.calcite.avatica.util.ArrayFactoryImpl;
import org.junit.jupiter.api.Test;
import java.sql.Array;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Types;
import java.util.List;
import java.util.TimeZone;
public class Asd
{
@Test
public void scalarInArrayWithStringToArray() throws SQLException
{
String connectionURL = "druidtest:///";
Connection connection = DriverManager.getConnection(connectionURL);
PreparedStatement stmt = connection
.prepareStatement("select l1 from numfoo where SCALAR_IN_ARRAY(l1,
STRING_TO_ARRAY(CAST(? as varchar),','))");
List<Integer> li = ImmutableList.of(0, 7);
String sqlArg = Joiner.on(",").join(li);
stmt.setString(1, sqlArg);
stmt.executeQuery();
ResultSet rs = stmt.getResultSet();
while (rs.next()) {
System.out.println(rs.getObject(1));
}
}
@Test
public void scalarInArrayNativeArray() throws SQLException
{
String connectionURL = "druidtest:///";
Connection connection = DriverManager.getConnection(connectionURL);
PreparedStatement stmt = connection.prepareStatement("select l1 from
numfoo where SCALAR_IN_ARRAY(l1, ?)");
Iterable<Object> li = ImmutableList.of(0, 7);
ArrayFactoryImpl a = new ArrayFactoryImpl(TimeZone.getDefault());
org.apache.calcite.avatica.proto.Common.AvaticaType proto;
AvaticaType type = ColumnMetaData.scalar(Types.INTEGER,
SqlType.INTEGER.name(), Rep.INTEGER);
Array arr = a.createArray(type, li);
stmt.setArray(1, arr);
stmt.executeQuery();
ResultSet rs = stmt.getResultSet();
while (rs.next()) {
System.out.println(rs.getObject(1));
}
}
}
```
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