[8.x] [ES|QL] Implicit casting string literal to intervals in EsqlScalarFunction and GroupingFunction (#115814)

docs/changelog/115814.yaml

@@ -0,0 +1,6 @@
+pr: 115814
+summary: "[ES|QL] Implicit casting string literal to intervals"
+area: ES|QL
+type: enhancement
+issues:
+ - 115352

docs/reference/esql/implicit-casting.asciidoc

@@ -5,7 +5,7 @@
 <titleabbrev>Implicit casting</titleabbrev>
 ++++
 
-Often users will input `datetime`, `ip`, `version`, or geospatial objects as simple strings in their queries for use in predicates, functions, or expressions. {esql} provides <<esql-type-conversion-functions, type conversion functions>> to explicitly convert these strings into the desired data types.
+Often users will input `date`, `ip`, `version`, `date_period` or `time_duration` as simple strings in their queries for use in predicates, functions, or expressions. {esql} provides <<esql-type-conversion-functions, type conversion functions>> to explicitly convert these strings into the desired data types.
 
 Without implicit casting users must explicitly code these `to_X` functions in their queries, when string literals don't match the target data types they are assigned or compared to. Here is an example of using `to_datetime` to explicitly perform a data type conversion.
 
@@ -18,7 +18,7 @@ FROM employees
 | LIMIT 1
 ----
 
-Implicit casting improves usability, by automatically converting string literals to the target data type. This is most useful when the target data type is `datetime`, `ip`, `version` or a geo spatial. It is natural to specify these as a string in queries.
+Implicit casting improves usability, by automatically converting string literals to the target data type. This is most useful when the target data type is `date`, `ip`, `version`, `date_period` or `time_duration`. It is natural to specify these as a string in queries.
 
 The first query can be coded without calling the `to_datetime` function, as follows:
 
@@ -38,16 +38,28 @@ The following table details which {esql} operations support implicit casting for
 
 [%header.monospaced.styled,format=dsv,separator=|]
 |===
-||ScalarFunction|BinaryComparison|ArithmeticOperation|InListPredicate|AggregateFunction
-|DATETIME|Y|Y|Y|Y|N
-|DOUBLE|Y|N|N|N|N
-|LONG|Y|N|N|N|N
-|INTEGER|Y|N|N|N|N
-|IP|Y|Y|Y|Y|N
-|VERSION|Y|Y|Y|Y|N
-|GEO_POINT|Y|N|N|N|N
-|GEO_SHAPE|Y|N|N|N|N
-|CARTESIAN_POINT|Y|N|N|N|N
-|CARTESIAN_SHAPE|Y|N|N|N|N
-|BOOLEAN|Y|Y|Y|Y|N
+||ScalarFunction*|Operator*|<<esql-group-functions, GroupingFunction>>|<<esql-agg-functions, AggregateFunction>>
+|DATE|Y|Y|Y|N
+|IP|Y|Y|Y|N
+|VERSION|Y|Y|Y|N
+|BOOLEAN|Y|Y|Y|N
+|DATE_PERIOD/TIME_DURATION|Y|N|Y|N
 |===
+
+ScalarFunction* includes:
+
+<<esql-conditional-functions-and-expressions, Conditional Functions and Expressions>>
+
+<<esql-date-time-functions, Date and Time Functions>>
+
+<<esql-ip-functions, IP Functions>>
+
+
+Operator* includes:
+
+<<esql-binary-operators, Binary Operators>>
+
+<<esql-unary-operators, Unary Operator>>
+
+<<esql-in-operator, IN>>
+

x-pack/plugin/esql-core/src/main/java/org/elasticsearch/xpack/esql/core/type/DataType.java

@@ -29,7 +29,6 @@
 import java.util.function.Function;
 
 import static java.util.stream.Collectors.toMap;
-import static java.util.stream.Collectors.toUnmodifiableMap;
 import static org.elasticsearch.xpack.esql.core.util.PlanStreamInput.readCachedStringWithVersionCheck;
 import static org.elasticsearch.xpack.esql.core.util.PlanStreamOutput.writeCachedStringWithVersionCheck;
 
@@ -276,7 +275,7 @@ public enum DataType {
 
     private static final Collection<DataType> STRING_TYPES = DataType.types().stream().filter(DataType::isString).toList();
 
-    private static final Map<String, DataType> NAME_TO_TYPE = TYPES.stream().collect(toUnmodifiableMap(DataType::typeName, t -> t));
+    private static final Map<String, DataType> NAME_TO_TYPE;
 
     private static final Map<String, DataType> ES_TO_TYPE;
 
@@ -287,6 +286,10 @@ public enum DataType {
         map.put("point", DataType.CARTESIAN_POINT);
         map.put("shape", DataType.CARTESIAN_SHAPE);
         ES_TO_TYPE = Collections.unmodifiableMap(map);
+        // DATETIME has different esType and typeName, add an entry in NAME_TO_TYPE with date as key
+        map = TYPES.stream().collect(toMap(DataType::typeName, t -> t));
+        map.put("date", DataType.DATETIME);
+        NAME_TO_TYPE = Collections.unmodifiableMap(map);
     }
 
     private static final Map<String, DataType> NAME_OR_ALIAS_TO_TYPE;

x-pack/plugin/esql/qa/testFixtures/src/main/resources/bucket.csv-spec

@@ -716,3 +716,47 @@ FROM employees
 2                      |1985-10-01T00:00:00.000Z
 4                      |1985-11-01T00:00:00.000Z
 ;
+
+bucketByWeekInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+FROM employees
+| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
+| STATS hires_per_week = COUNT(*) BY week = BUCKET(hire_date, "1 week")
+| SORT week
+;
+
+  hires_per_week:long    |    week:date
+2                        |1985-02-18T00:00:00.000Z
+1                        |1985-05-13T00:00:00.000Z
+1                        |1985-07-08T00:00:00.000Z
+1                        |1985-09-16T00:00:00.000Z
+2                        |1985-10-14T00:00:00.000Z
+4                        |1985-11-18T00:00:00.000Z
+;
+
+bucketByMinuteInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM sample_data
+| STATS min = min(@timestamp), max = MAX(@timestamp) BY bucket = BUCKET(@timestamp, "30 minutes")
+| SORT min
+;
+
+          min:date      |          max:date      |         bucket:date
+2023-10-23T12:15:03.360Z|2023-10-23T12:27:28.948Z|2023-10-23T12:00:00.000Z
+2023-10-23T13:33:34.937Z|2023-10-23T13:55:01.543Z|2023-10-23T13:30:00.000Z
+;
+
+bucketByMonthInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM sample_data
+| EVAL adjusted = CASE(TO_LONG(@timestamp) % 2 == 0, @timestamp + 1 month, @timestamp + 2 years)
+| STATS c = COUNT(*) BY b = BUCKET(adjusted, "1 month")
+| SORT c
+;
+
+c:long |b:date
+3      |2025-10-01T00:00:00.000Z
+4      |2023-11-01T00:00:00.000Z
+;

x-pack/plugin/esql/qa/testFixtures/src/main/resources/date.csv-spec

@@ -1286,3 +1286,108 @@ ROW a = GREATEST(TO_DATETIME("1957-05-23T00:00:00Z"), TO_DATETIME("1958-02-19T00
 a:datetime
 1958-02-19T00:00:00
 ;
+
+evalDateTruncMonthInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM employees
+| SORT hire_date
+| EVAL x = date_trunc("1 month", hire_date)
+| KEEP emp_no, hire_date, x
+| LIMIT 5;
+
+emp_no:integer | hire_date:date                | x:date
+10009          | 1985-02-18T00:00:00.000Z      | 1985-02-01T00:00:00.000Z
+10048          | 1985-02-24T00:00:00.000Z      | 1985-02-01T00:00:00.000Z
+10098          | 1985-05-13T00:00:00.000Z      | 1985-05-01T00:00:00.000Z
+10076          | 1985-07-09T00:00:00.000Z      | 1985-07-01T00:00:00.000Z
+10061          | 1985-09-17T00:00:00.000Z      | 1985-09-01T00:00:00.000Z
+;
+
+evalDateTruncHourInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM employees
+| SORT hire_date
+| EVAL x = date_trunc("240 hours", hire_date)
+| KEEP emp_no, hire_date, x
+| LIMIT 5;
+
+emp_no:integer | hire_date:date                | x:date
+10009          | 1985-02-18T00:00:00.000Z      | 1985-02-11T00:00:00.000Z
+10048          | 1985-02-24T00:00:00.000Z      | 1985-02-21T00:00:00.000Z
+10098          | 1985-05-13T00:00:00.000Z      | 1985-05-12T00:00:00.000Z
+10076          | 1985-07-09T00:00:00.000Z      | 1985-07-01T00:00:00.000Z
+10061          | 1985-09-17T00:00:00.000Z      | 1985-09-09T00:00:00.000Z
+;
+
+evalDateTruncDayInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM sample_data
+| SORT @timestamp ASC
+| EVAL t = DATE_TRUNC("1 day", @timestamp)
+| KEEP t;
+
+t:date
+2023-10-23T00:00:00
+2023-10-23T00:00:00
+2023-10-23T00:00:00
+2023-10-23T00:00:00
+2023-10-23T00:00:00
+2023-10-23T00:00:00
+2023-10-23T00:00:00
+;
+
+evalDateTruncMinuteInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM sample_data
+| SORT @timestamp ASC
+| EVAL t = DATE_TRUNC("1 minute", @timestamp)
+| KEEP t;
+
+t:date
+2023-10-23T12:15:00
+2023-10-23T12:27:00
+2023-10-23T13:33:00
+2023-10-23T13:51:00
+2023-10-23T13:52:00
+2023-10-23T13:53:00
+2023-10-23T13:55:00
+;
+
+evalDateTruncDayInStringNull
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM employees
+| WHERE emp_no == 10040
+| EVAL x = date_trunc("1 day", birth_date)
+| KEEP emp_no, birth_date, x;
+
+emp_no:integer | birth_date:date               | x:date
+10040          | null                          | null
+;
+
+evalDateTruncYearInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+ROW a = 1
+| EVAL year_hired = DATE_TRUNC("1 year", "1991-06-26T00:00:00.000Z")
+;
+
+a:integer | year_hired:date
+1         | 1991-01-01T00:00:00.000Z
+;
+
+filteringWithTemporalAmountInString
+required_capability: implicit_casting_string_literal_to_temporal_amount
+
+FROM employees
+| SORT emp_no
+| WHERE birth_date < "2024-01-01" - 70 years
+| STATS cnt = count(*);
+
+cnt:long
+19
+;

x-pack/plugin/esql/src/main/java/org/elasticsearch/xpack/esql/action/EsqlCapabilities.java

@@ -475,7 +475,12 @@ public enum Cap {
          * - Introduce BinaryPlan and co
          * - Refactor INLINESTATS and LOOKUP as a JOIN block
          */
-        JOIN_PLANNING_V1(Build.current().isSnapshot());
+        JOIN_PLANNING_V1(Build.current().isSnapshot()),
+
+        /**
+         * Support implicit casting from string literal to DATE_PERIOD or TIME_DURATION.
+         */
+        IMPLICIT_CASTING_STRING_LITERAL_TO_TEMPORAL_AMOUNT;
 
         private final boolean enabled;