【spark系列4】spark 3.0.1集成delta 0.7.0原理解析--delta自定义sql

前提

本文基于 spark 3.0.1
delta 0.7.0
我们都知道delta.io是一个给数据湖提供可靠性的开源存储层的软件，关于他的用处，可以参考Delta Lake，让你从复杂的Lambda架构中解放出来,于此类似的产品有hudi,Iceberg,因为delta无缝集成spark，所以我们来分析一下delta集成spark的内部原理以及框架，对于spark 3.x 与delta的集成是分两部分的，一部分是delta自定义的sql语法，另一部分是基于Catalog plugin API的DDL DML sql操作(spark 3.x以前是不支持的).
我们今天先分析第一部分 delta自定义的sql语法

分析

我们从delta的configurate sparksession入手,如下:

import org.apache.spark.sql.SparkSession

val spark = SparkSession
  .builder()
  .appName("...")
  .master("...")
  .config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension")
  .config("spark.sql.catalog.spark_catalog", "org.apache.spark.sql.delta.catalog.DeltaCatalog")
  .getOrCreate()

我们可以看到 config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension")
从spark configuration,我们可以看到对该spark.sql.extensions的解释是

A comma-separated list of classes that implement Function1[SparkSessionExtensions, Unit] used to configure Spark Session extensions. The classes must have a no-args constructor. If multiple extensions are specified, they are applied in the specified order. For the case of rules and planner strategies, they are applied in the specified order. For the case of parsers, the last parser is used and each parser can delegate to its predecessor. For the case of function name conflicts, the last registered function name is used.

一句话就是用来对sparksession的扩展，可以对spark sql的逻辑计划进行扩展，且这个功能从spark 2.2.0就有了
看一下io.delta.sql.DeltaSparkSessionExtension类

class DeltaSparkSessionExtension extends (SparkSessionExtensions => Unit) {
  override def apply(extensions: SparkSessionExtensions): Unit = {
    extensions.injectParser { (session, parser) =>
      new DeltaSqlParser(parser)
    }
    extensions.injectResolutionRule { session =>
      new DeltaAnalysis(session, session.sessionState.conf)
    }
    extensions.injectCheckRule { session =>
      new DeltaUnsupportedOperationsCheck(session)
    }
    extensions.injectPostHocResolutionRule { session =>
      new PreprocessTableUpdate(session.sessionState.conf)
    }
    extensions.injectPostHocResolutionRule { session =>
      new PreprocessTableMerge(session.sessionState.conf)
    }
    extensions.injectPostHocResolutionRule { session =>
      new PreprocessTableDelete(session.sessionState.conf)
    }
  }
}

DeltaSqlParser class就是delta对于自身语法的支持，那到底怎么支持以及支持什么呢？
我们看一下extensions.injectParser代码

 private[this] val parserBuilders = mutable.Buffer.empty[ParserBuilder]

  private[sql] def buildParser(
      session: SparkSession,
      initial: ParserInterface): ParserInterface = {
    parserBuilders.foldLeft(initial) { (parser, builder) =>
      builder(session, parser)
    }
  }

  /**
   * Inject a custom parser into the [[SparkSession]]. Note that the builder is passed a session
   * and an initial parser. The latter allows for a user to create a partial parser and to delegate
   * to the underlying parser for completeness. If a user injects more parsers, then the parsers
   * are stacked on top of each other.
   */
  def injectParser(builder: ParserBuilder): Unit = {
    parserBuilders += builder
  }

我们看到buildParser方法对我们传入的DeltaSqlParser进行了方法的初始化，也就是说DeltaSqlParser 的delegate变量被赋值为initial,
而该buildParser方法 被BaseSessionStateBuilder调用：

 /**
   * Parser that extracts expressions, plans, table identifiers etc. from SQL texts.
   *
   * Note: this depends on the `conf` field.
   */
  protected lazy val sqlParser: ParserInterface = {
    extensions.buildParser(session, new SparkSqlParser(conf))
  }

所以说initial的实参是SparkSqlParser，也就是SparkSqlParser成了DeltaSqlParser代理，我们再看看DeltaSqlParser的方法:

override def parsePlan(sqlText: String): LogicalPlan = parse(sqlText) { parser =>
    builder.visit(parser.singleStatement()) match {
      case plan: LogicalPlan => plan
      case _ => delegate.parsePlan(sqlText)
    }
  }

这里涉及到了antlr4的语法，也就是说对于逻辑计划的解析,如自身DeltaSqlParser能够解析，就进行解析，不能的话就委托给SparkSqlParser进行解析，而解析是该类DeltaSqlAstBuilder的功能：

class DeltaSqlAstBuilder extends DeltaSqlBaseBaseVisitor[AnyRef] {

  /**
   * Create a [[VacuumTableCommand]] logical plan. Example SQL:
   * {{{
   *   VACUUM ('/path/to/dir' | delta.`/path/to/dir`) [RETAIN number HOURS] [DRY RUN];
   * }}}
   */
  override def visitVacuumTable(ctx: VacuumTableContext): AnyRef = withOrigin(ctx) {
    VacuumTableCommand(
      Option(ctx.path).map(string),
      Option(ctx.table).map(visitTableIdentifier),
      Option(ctx.number).map(_.getText.toDouble),
      ctx.RUN != null)
  }

  override def visitDescribeDeltaDetail(
      ctx: DescribeDeltaDetailContext): LogicalPlan = withOrigin(ctx) {
    DescribeDeltaDetailCommand(
      Option(ctx.path).map(string),
      Option(ctx.table).map(visitTableIdentifier))
  }

  override def visitDescribeDeltaHistory(
      ctx: DescribeDeltaHistoryContext): LogicalPlan = withOrigin(ctx) {
    DescribeDeltaHistoryCommand(
      Option(ctx.path).map(string),
      Option(ctx.table).map(visitTableIdentifier),
      Option(ctx.limit).map(_.getText.toInt))
  }

  override def visitGenerate(ctx: GenerateContext): LogicalPlan = withOrigin(ctx) {
    DeltaGenerateCommand(
      modeName = ctx.modeName.getText,
      tableId = visitTableIdentifier(ctx.table))
  }

  override def visitConvert(ctx: ConvertContext): LogicalPlan = withOrigin(ctx) {
    ConvertToDeltaCommand(
      visitTableIdentifier(ctx.table),
      Option(ctx.colTypeList).map(colTypeList => StructType(visitColTypeList(colTypeList))),
      None)
  }

  override def visitSingleStatement(ctx: SingleStatementContext): LogicalPlan = withOrigin(ctx) {
    visit(ctx.statement).asInstanceOf[LogicalPlan]
  }

  protected def visitTableIdentifier(ctx: QualifiedNameContext): TableIdentifier = withOrigin(ctx) {
    ctx.identifier.asScala match {
      case Seq(tbl) => TableIdentifier(tbl.getText)
      case Seq(db, tbl) => TableIdentifier(tbl.getText, Some(db.getText))
      case _ => throw new ParseException(s"Illegal table name ${ctx.getText}", ctx)
    }
  }

  override def visitPassThrough(ctx: PassThroughContext): LogicalPlan = null
}

那这些方法比如visitVacuumTable，visitDescribeDeltaDetail是从哪里来的呢？
咱们看看DeltaSqlBase.g4:

singleStatement
    : statement EOF
    ;

// If you add keywords here that should not be reserved, add them to 'nonReserved' list.
statement
    : VACUUM (path=STRING | table=qualifiedName)
        (RETAIN number HOURS)? (DRY RUN)?                               #vacuumTable
    | (DESC | DESCRIBE) DETAIL (path=STRING | table=qualifiedName)      #describeDeltaDetail
    | GENERATE modeName=identifier FOR TABLE table=qualifiedName        #generate
    | (DESC | DESCRIBE) HISTORY (path=STRING | table=qualifiedName)
        (LIMIT limit=INTEGER_VALUE)?                                    #describeDeltaHistory
    | CONVERT TO DELTA table=qualifiedName
        (PARTITIONED BY '(' colTypeList ')')?                           #convert
    | .*?                                                               #passThrough
    ;

这里涉及到的antlr4语法，不会的可以自行网上查阅。注意一下spark 和delta用到的都是visit的模式。
再来对于一下delta官网提供的操作 :

Vacuum
Describe History
Describe Detail
Generate
Convert to Delta
Convert Delta table to a Parquet table

这样就能对应上了，如Vacuum操作对应vacuumTable,Convert to Delta对应 convert.

其实delta支持拓展了spark，我们也可按照delta的方式，对spark进行扩展，从而实现自己的sql语法