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12 changes: 12 additions & 0 deletions common/utils/src/main/resources/error/error-conditions.json
Original file line number Diff line number Diff line change
Expand Up @@ -191,6 +191,18 @@
],
"sqlState" : "0A000"
},
"AUTOCDC_COLUMNS_NOT_FOUND_IN_SCHEMA" : {
"message" : [
"Using <caseSensitivity> column name comparison, the following columns are not present in the <schemaName> schema: <missingColumns>. Available columns: <availableColumns>."
],
"sqlState" : "42703"
},
"AUTOCDC_MULTIPART_COLUMN_IDENTIFIER" : {
"message" : [
"Expected a single column identifier; got the multi-part identifier <columnName> (parts: <nameParts>)."
],
"sqlState" : "42703"
},
"AVRO_CANNOT_WRITE_NULL_FIELD" : {
"message" : [
"Cannot write null value for field <name> defined as non-null Avro data type <dataType>.",
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,159 @@
/*
* 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.pipelines.autocdc

import org.apache.spark.sql.{AnalysisException, Column}
import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
import org.apache.spark.sql.catalyst.util.QuotingUtils
import org.apache.spark.sql.types.StructType

/**
* A single, unqualified column identifier (no nested path or table/alias qualifier). Backticks
* are consumed: "`a.b`" is stored as "a.b" in [[name]]. Use [[name]] for direct schema-fieldName
* comparison and [[quoted]] for APIs that re-parse identifier strings.
*/
case class UnqualifiedColumnName private (name: String) {
def quoted: String = QuotingUtils.quoteIdentifier(name)
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}

object UnqualifiedColumnName {
def apply(input: String): UnqualifiedColumnName = {
val nameParts = CatalystSqlParser.parseMultipartIdentifier(input)
if (nameParts.length != 1) {
throw multipartColumnIdentifierError(input, nameParts)
}
new UnqualifiedColumnName(nameParts.head)
}

private def multipartColumnIdentifierError(
columnName: String,
nameParts: Seq[String]
): AnalysisException =
new AnalysisException(
errorClass = "AUTOCDC_MULTIPART_COLUMN_IDENTIFIER",
messageParameters = Map(
"columnName" -> columnName,
"nameParts" -> nameParts.mkString(", ")
)
)
}

sealed trait ColumnSelection
object ColumnSelection {

case class IncludeColumns(columns: Seq[UnqualifiedColumnName]) extends ColumnSelection
case class ExcludeColumns(columns: Seq[UnqualifiedColumnName])
extends ColumnSelection

/**
* Applies [[ColumnSelection]] to a [[StructType]] and returns the filtered schema. Field order
* follows the original schema; only matching fields are retained in the returned schema.
*
* @param schemaName Logical name of the schema being filtered, surfaced in error messages
* when columns are not found (e.g. "microbatch", "target").
* @param schema The schema to filter.
* @param columnSelection The user-provided selection. `None` is a no-op and returns `schema`
* unchanged.
* @param caseSensitive Whether to match column names case-sensitively against the schema.
* Callers should derive this from the session, e.g.
* `session.sessionState.conf.caseSensitiveAnalysis`, so column matching
* stays consistent with `spark.sql.caseSensitive`.
*/
def applyToSchema(
schemaName: String,
schema: StructType,
columnSelection: Option[ColumnSelection],
caseSensitive: Boolean): StructType = columnSelection match {
case None =>
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// A None column selection is interpreted as a no-op.
schema
case Some(IncludeColumns(cols)) =>
val keepIndices = lookupFieldIndices(schemaName, schema, cols, caseSensitive)
StructType(schema.fields.zipWithIndex.collect {
case (field, idx) if keepIndices.contains(idx) => field
})
case Some(ExcludeColumns(cols)) =>
val dropIndices = lookupFieldIndices(schemaName, schema, cols, caseSensitive)
StructType(schema.fields.zipWithIndex.collect {
case (field, idx) if !dropIndices.contains(idx) => field
})
}

private def lookupFieldIndices(
schemaName: String,
schema: StructType,
fields: Seq[UnqualifiedColumnName],
caseSensitive: Boolean): Set[Int] = {
val caseAwareGetFieldIndex: String => Option[Int] =
if (caseSensitive) schema.getFieldIndex else schema.getFieldIndexCaseInsensitive

val fieldIndexResolutions = fields.map(f => f -> caseAwareGetFieldIndex(f.name))
val missingFieldNames = fieldIndexResolutions.collect { case (f, None) => f.name }.distinct
if (missingFieldNames.nonEmpty) {
throw new AnalysisException(
errorClass = "AUTOCDC_COLUMNS_NOT_FOUND_IN_SCHEMA",
messageParameters = Map(
"caseSensitivity" -> CaseSensitivityLabels.of(caseSensitive),
"schemaName" -> schemaName,
"missingColumns" -> missingFieldNames.mkString(", "),
"availableColumns" -> schema.fieldNames.mkString(", ")
)
)
}
fieldIndexResolutions.flatMap { case (_, idx) => idx }.toSet
}
}

/** User-facing case-sensitivity labels surfaced in AutoCDC error messages. */
private[autocdc] object CaseSensitivityLabels {
val CaseSensitive: String = "case-sensitive"
val CaseInsensitive: String = "case-insensitive"

def of(caseSensitive: Boolean): String =
if (caseSensitive) CaseSensitive else CaseInsensitive
}

/** The SCD (Slowly Changing Dimension) strategy for a CDC flow. */
sealed trait ScdType

object ScdType {
/** Representation for the standard SCD1 strategy. */
case object Type1 extends ScdType

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should we scaladoc type1, type2?

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Corresponds to the industry standard definitions for SCD1/SCD2 so I won't document exactly what those algorithms entail, but added a basic scaladoc that Type1 <=> SCD1 and Type2 <=> SCD2.

/** Representation for the standard SCD2 strategy. */
case object Type2 extends ScdType
}

/**
* Configuration for an AutoCDC flow.
*
* @param keys The column(s) that uniquely identify a row in the source data.
* @param sequencing Expression ordering CDC events to correctly resolve out-of-order
* arrivals. Must be a sortable type.
* @param deleteCondition Expression that marks a source row as a DELETE. When None, all
* rows are treated as upserts.
* @param storedAsScdType The SCD strategy these args should be applied to.
* @param columnSelection Which source columns to select in the target table. None means
* all columns.
*/
case class ChangeArgs(
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keys: Seq[UnqualifiedColumnName],
sequencing: Column,
storedAsScdType: ScdType,
deleteCondition: Option[Column] = None,
columnSelection: Option[ColumnSelection] = None
)
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