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[Backport 2.19-dev] Support using decimal as span literals #4799

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Merged
yuancu merged 1 commit into from
Nov 14, 2025
Merged

[Backport 2.19-dev] Support using decimal as span literals #4799

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20 changes: 16 additions & 4 deletions core/src/main/java/org/opensearch/sql/expression/function/udf/SpanFunction.java
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@
import org.apache.calcite.schema.impl.ScalarFunctionImpl;
import org.apache.calcite.sql.type.CompositeOperandTypeChecker;
import org.apache.calcite.sql.type.OperandTypes;
import org.apache.calcite.sql.type.ReturnTypes;
import org.apache.calcite.sql.type.SqlReturnTypeInference;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.calcite.sql.type.SqlTypeFamily;
Expand All @@ -45,7 +44,17 @@ public SpanFunction() {

@Override
public SqlReturnTypeInference getReturnTypeInference() {
return ReturnTypes.ARG0;
// Return arg0 type if it has a unit (i.e. time related span)
return callBinding -> {
if (SqlTypeUtil.isString(callBinding.getOperandType(2))) {
return callBinding.getOperandType(0);
}
// Use the least restrictive type between the field type and the interval type if it's a
// numeric span. E.g. span(int_field, double_literal) -> double
return callBinding
.getTypeFactory()
.leastRestrictive(List.of(callBinding.getOperandType(0), callBinding.getOperandType(1)));
};
}

@Override
Expand All @@ -57,10 +66,9 @@ public UDFOperandMetadata getOperandMetadata() {
.or(
OperandTypes.family(
SqlTypeFamily.DATETIME, SqlTypeFamily.NUMERIC, SqlTypeFamily.CHARACTER))
// TODO: numeric span should support decimal as its interval
.or(
OperandTypes.family(
SqlTypeFamily.NUMERIC, SqlTypeFamily.INTEGER, SqlTypeFamily.ANY)));
SqlTypeFamily.NUMERIC, SqlTypeFamily.NUMERIC, SqlTypeFamily.ANY)));
}

public static class SpanImplementor implements NotNullImplementor {
Expand All @@ -73,8 +81,12 @@ public Expression implement(
Expression interval = translatedOperands.get(1);

RelDataType fieldType = call.getOperands().get(0).getType();
RelDataType intervalType = call.getOperands().get(1).getType();
RelDataType unitType = call.getOperands().get(2).getType();

if (SqlTypeUtil.isDecimal(intervalType)) {
interval = Expressions.call(interval, "doubleValue");
}
if (SqlTypeUtil.isNull(unitType)) {
SqlTypeName sqlTypeName = call.getType().getSqlTypeName();
Expression result;
Expand Down
8 changes: 8 additions & 0 deletions integ-test/src/test/java/org/opensearch/sql/calcite/remote/CalciteBinCommandIT.java
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Expand Up @@ -1068,4 +1068,12 @@ public void testBinWithEvalCreatedDottedFieldName() throws IOException {
rows(false, "go", "opentelemetry", 16, 1, "12-14"),
rows(true, "rust", "opentelemetry", 12, 1, "14-16"));
}

@Test
public void testBinWithDecimalSpan() throws IOException {
JSONObject result =
executeQuery("source=events_null | bin cpu_usage span=7.5 | stats count() by cpu_usage");
verifySchema(result, schema("count()", "bigint"), schema("cpu_usage", "string"));
verifyDataRows(result, rows(3, "37.5-45.0"), rows(2, "45.0-52.5"), rows(1, "52.5-60.0"));
}
}
17 changes: 17 additions & 0 deletions integ-test/src/test/java/org/opensearch/sql/ppl/StatsCommandIT.java
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Expand Up @@ -1217,4 +1217,21 @@ public void testStatsSortOnMeasureComplex() throws IOException {
resetQueryBucketSize();
}
}

@Test
public void testStatsByFractionalSpan() throws IOException {
JSONObject response1 =
executeQuery(
String.format(
"source=%s | stats count by span(balance, 4170.5)",
TEST_INDEX_BANK_WITH_NULL_VALUES));
verifySchema(response1, schema("count", "bigint"), schema("span(balance,4170.5)", "double"));
verifyDataRows(
response1,
rows(3, null),
rows(1, 4170.5),
rows(1, 29193.5),
rows(1, 37534.5),
rows(1, 45875.5));
}
}
39 changes: 17 additions & 22 deletions ppl/src/main/antlr/OpenSearchPPLLexer.g4
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Expand Up @@ -521,40 +521,35 @@ ALIGNTIME: 'ALIGNTIME';
// Must precede ID to avoid conflicts with identifier matching
PERCENTILE_SHORTCUT: PERC(INTEGER_LITERAL | DECIMAL_LITERAL) | 'P'(INTEGER_LITERAL | DECIMAL_LITERAL);

SPANLENGTH: [0-9]+ (
'US' |'CS'|'DS'
|'MS'|'MILLISECOND'|'MILLISECONDS'
|'S'|'SEC'|'SECS'|'SECOND'|'SECONDS'
|'MIN'|'MINS'|'MINUTE'|'MINUTES'
|'H'|'HR'|'HRS'|'HOUR'|'HOURS'
|'H'|'HR'|'HRS'|'HOUR'|'HOURS'
|'D'|'DAY'|'DAYS'
|'W'|'WEEK'|'WEEKS'
|'M'|'MON'|'MONTH'|'MONTHS'
|'Q'|'QTR'|'QTRS'|'QUARTER'|'QUARTERS'
|'Y'|'YR'|'YRS'|'YEAR'|'YEARS'
);
fragment DAY_OR_DOUBLE: 'D';
fragment COMMON_TIME_UNIT: 'S'|'SEC'|'SECOND'
|'M'|'MIN'|'MINUTE'
|'H'|'HR'|'HOUR'
|'DAY'|'W'|'WEEK'
|'MON'|'MONTH'
|'Q'|'QTR'|'QUARTER'
|'Y'|'YR'|'YEAR';
fragment PLURAL_UNIT: 'MILLISECONDS'|'SECS'|'SECONDS'|'MINS'|'MINUTES'|'HRS'|'HOURS'
|'DAYS'|'WEEKS'|'MONTHS'|'QTRS'|'QUARTERS'|'YRS'|'YEARS';
fragment SPANUNIT: COMMON_TIME_UNIT | PLURAL_UNIT
|'US'|'CS'|'DS'
|'MS'|'MILLISECOND';
SPANLENGTH: DEC_DIGIT+ (SPANUNIT | DAY_OR_DOUBLE);
DECIMAL_SPANLENGTH: (DEC_DIGIT+)? '.' DEC_DIGIT+ SPANUNIT;

NUMERIC_ID : DEC_DIGIT+ ID_LITERAL;

// LITERALS AND VALUES
//STRING_LITERAL: DQUOTA_STRING | SQUOTA_STRING | BQUOTA_STRING;
fragment WEEK_SNAP_UNIT: 'W' [0-7];
fragment TIME_SNAP_UNIT: 'S' | 'SEC' | 'SECOND'
| 'M' | 'MIN' | 'MINUTE'
| 'H' | 'HR' | 'HOUR' | 'HOURS'
| 'D' | 'DAY'
| 'W' | 'WEEK' | WEEK_SNAP_UNIT
| 'MON' | 'MONTH'
| 'Q' | 'QTR' | 'QUARTER'
| 'Y' | 'YR' | 'YEAR';
fragment TIME_SNAP_UNIT: COMMON_TIME_UNIT | WEEK_SNAP_UNIT | DAY_OR_DOUBLE;
TIME_SNAP: AT TIME_SNAP_UNIT;
ID: ID_LITERAL;
CLUSTER: CLUSTER_PREFIX_LITERAL;
INTEGER_LITERAL: DEC_DIGIT+;
DECIMAL_LITERAL: (DEC_DIGIT+)? '.' DEC_DIGIT+;
FLOAT_LITERAL: (DEC_DIGIT+)? '.' DEC_DIGIT+ 'F';
DOUBLE_LITERAL: (DEC_DIGIT+)? '.' DEC_DIGIT+ 'D';
DOUBLE_LITERAL: (DEC_DIGIT+)? '.' DEC_DIGIT+ DAY_OR_DOUBLE;

fragment DATE_SUFFIX: ([\-.][*0-9]+)+;
fragment CLUSTER_PREFIX_LITERAL: [*A-Z]+?[*A-Z_\-0-9]* COLON;
Expand Down
3 changes: 3 additions & 0 deletions ppl/src/main/antlr/OpenSearchPPLParser.g4
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Expand Up @@ -336,7 +336,10 @@ timechartParameter

spanLiteral
: SPANLENGTH
| DECIMAL_SPANLENGTH
| DOUBLE_LITERAL // 1.5d can also represent decimal span length
| INTEGER_LITERAL
| DECIMAL_LITERAL
;

evalCommand
Expand Down
9 changes: 9 additions & 0 deletions ppl/src/main/java/org/opensearch/sql/ppl/parser/AstExpressionBuilder.java
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Expand Up @@ -824,6 +824,15 @@ private List<UnresolvedExpression> multiFieldRelevanceArguments(
public UnresolvedExpression visitSpanLiteral(OpenSearchPPLParser.SpanLiteralContext ctx) {
if (ctx.INTEGER_LITERAL() != null) {
return AstDSL.intLiteral(Integer.parseInt(ctx.INTEGER_LITERAL().getText()));
} else if (ctx.DECIMAL_LITERAL() != null) {
return AstDSL.decimalLiteral(new BigDecimal(ctx.DECIMAL_LITERAL().getText()));
} else if (ctx.DECIMAL_SPANLENGTH() != null || ctx.DOUBLE_LITERAL() != null) {
throw new IllegalArgumentException(
StringUtils.format(
"Span length [%s] is invalid: floating-point time intervals are not supported.",
ctx.DECIMAL_SPANLENGTH() != null
? ctx.DECIMAL_SPANLENGTH().getText()
: ctx.DOUBLE_LITERAL().getText()));
} else {
return AstDSL.stringLiteral(ctx.getText());
}
Expand Down
20 changes: 20 additions & 0 deletions ppl/src/test/java/org/opensearch/sql/ppl/parser/AstBuilderTest.java
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Expand Up @@ -1606,4 +1606,24 @@ public void testChartCommandWithBottomLimit() {
exprList(argument("limit", intLiteral(3)), argument("top", booleanLiteral(false))))
.build());
}

@Test
public void testTimeSpanWithDecimalShouldThrow() {
Throwable t1 =
assertThrows(
IllegalArgumentException.class, () -> plan("source=t | timechart span=1.5d count"));
assertTrue(
t1.getMessage()
.contains(
"Span length [1.5d] is invalid: floating-point time intervals are not supported."));

Throwable t2 =
assertThrows(
IllegalArgumentException.class,
() -> plan("source=t | stats count by span(@timestamp, 2.5y)"));
assertTrue(
t2.getMessage()
.contains(
"Span length [2.5y] is invalid: floating-point time intervals are not supported."));
}
}
13 changes: 13 additions & 0 deletions ppl/src/test/java/org/opensearch/sql/ppl/parser/AstExpressionBuilderTest.java
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Expand Up @@ -1655,6 +1655,19 @@ public void testVisitSpanLiteral() {
exprList(
argument("limit", intLiteral(10)), argument("useother", booleanLiteral(true))))
.build());

// Test span literal with decimal value
assertEqual(
"source=events_null | bin cpu_usage span=7.5 | stats count() by cpu_usage",
agg(
bin(
relation("events_null"),
field("cpu_usage"),
argument("span", decimalLiteral(new java.math.BigDecimal("7.5")))),
exprList(alias("count()", aggregate("count", allFields()))),
emptyList(),
exprList(alias("cpu_usage", field("cpu_usage"))),
defaultStatsArgs()));
}

@Test
Expand Down
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