stevomitric commented on code in PR #56266: URL: https://github.com/apache/spark/pull/56266#discussion_r3340625085
########## sql/api/src/main/scala/org/apache/spark/sql/types/ops/TimestampNanosTypeApiOps.scala: ########## @@ -0,0 +1,91 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.types.ops + +import org.apache.spark.SparkException +import org.apache.spark.sql.AnalysisException +import org.apache.spark.sql.catalyst.encoders.AgnosticEncoder +import org.apache.spark.sql.errors.DataTypeErrorsBase +import org.apache.spark.sql.types.{TimestampLTZNanosType, TimestampNTZNanosType} + +/** + * Client-side (spark-api) operations shared by the nanosecond timestamp types + * (TimestampNTZNanosType and TimestampLTZNanosType). + * + * Internal values are [[org.apache.spark.unsafe.types.TimestampNanosVal]] (epoch micros + nanos + * within the micro). The two concrete subclasses differ only in their DataType and SQL-literal + * prefix; storage and formatting are identical. + * + * SCOPE (SPARK-57207): this issue wires physical representation, literals, row accessors, and + * codegen class selection. String formatting is not yet implemented: format() throws an internal + * error so callers get a clear message rather than a debug string; dedicated fractional-second + * formatters land in a follow-up issue. + * Dataset encoders are out of scope (SPARK-57033 and related), so getEncoder reports the type as + * unsupported, matching the legacy RowEncoder behavior. + * + * @since 4.3.0 + */ +abstract class TimestampNanosTypeApiOps extends TypeApiOps with DataTypeErrorsBase { + + /** SQL literal prefix for this type, e.g. "TIMESTAMP_NTZ" or "TIMESTAMP_LTZ". */ + protected def sqlTypeName: String + + // ==================== String Formatting ==================== + + // String formatting of nanosecond timestamps is not yet implemented (follow-up after + // SPARK-57207). Throw an internal error so that callers see a clear message rather than a + // debug toString from TimestampNanosVal. + override def format(v: Any): String = + throw SparkException.internalError( + s"Formatting of ${dataType.typeName} is not yet implemented.") Review Comment: Will casting to string throw different errors when types framework is on/off now? This is an internal exception. ########## sql/api/src/main/scala/org/apache/spark/sql/types/ops/TimestampNanosTypeApiOps.scala: ########## @@ -0,0 +1,91 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.types.ops + +import org.apache.spark.SparkException +import org.apache.spark.sql.AnalysisException +import org.apache.spark.sql.catalyst.encoders.AgnosticEncoder +import org.apache.spark.sql.errors.DataTypeErrorsBase +import org.apache.spark.sql.types.{TimestampLTZNanosType, TimestampNTZNanosType} + +/** + * Client-side (spark-api) operations shared by the nanosecond timestamp types + * (TimestampNTZNanosType and TimestampLTZNanosType). + * + * Internal values are [[org.apache.spark.unsafe.types.TimestampNanosVal]] (epoch micros + nanos + * within the micro). The two concrete subclasses differ only in their DataType and SQL-literal + * prefix; storage and formatting are identical. + * + * SCOPE (SPARK-57207): this issue wires physical representation, literals, row accessors, and + * codegen class selection. String formatting is not yet implemented: format() throws an internal + * error so callers get a clear message rather than a debug string; dedicated fractional-second + * formatters land in a follow-up issue. + * Dataset encoders are out of scope (SPARK-57033 and related), so getEncoder reports the type as + * unsupported, matching the legacy RowEncoder behavior. + * + * @since 4.3.0 + */ +abstract class TimestampNanosTypeApiOps extends TypeApiOps with DataTypeErrorsBase { + + /** SQL literal prefix for this type, e.g. "TIMESTAMP_NTZ" or "TIMESTAMP_LTZ". */ + protected def sqlTypeName: String + + // ==================== String Formatting ==================== + + // String formatting of nanosecond timestamps is not yet implemented (follow-up after + // SPARK-57207). Throw an internal error so that callers see a clear message rather than a + // debug toString from TimestampNanosVal. + override def format(v: Any): String = + throw SparkException.internalError( + s"Formatting of ${dataType.typeName} is not yet implemented.") + + override def toSQLValue(v: Any): String = s"$sqlTypeName '${format(v)}'" + + // ==================== Row Encoding ==================== + + // Encoders are handled in a follow-up issue (SPARK-57033). Until then, report the type as + // unsupported with the same error as the legacy RowEncoder fallback to preserve parity. + override def getEncoder: AgnosticEncoder[_] = + throw new AnalysisException( + errorClass = "UNSUPPORTED_DATA_TYPE_FOR_ENCODER", + messageParameters = Map("dataType" -> toSQLType(dataType))) Review Comment: Didn't we implement encoders for TimestampNano in `AgnosticEncoder.scala`? ``` case class LocalDateTimeNanosEncoder(precision: Int) extends LeafEncoder[LocalDateTime](TimestampNTZNanosType(precision)) ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
