StreamTableEnvironment
该类包含sql解析、验证、优化、执行等各环节需要的元数据管理器CatalogManager,模块管理器(模块包含函数集、类型集、规则集)moduleManager，用户自定义函数管理器FunctionCatalog,线程池、sql解析器Planner。
StreamTableEnvironmentImpl.create(executionEnvironment, settings, new TableConfig)
def create(
executionEnvironment: StreamExecutionEnvironment,
settings: EnvironmentSettings,
tableConfig: TableConfig)
: StreamTableEnvironmentImpl = {
val catalogManager = new CatalogManager(
settings.getBuiltInCatalogName,
new GenericInMemoryCatalog(settings.getBuiltInCatalogName, settings.getBuiltInDatabaseName))
val moduleManager = new ModuleManager
val functionCatalog = new FunctionCatalog(catalogManager, moduleManager)
val executorProperties = settings.toExecutorProperties
val executor = lookupExecutor(executorProperties, executionEnvironment)
val plannerProperties = settings.toPlannerProperties
val planner = ComponentFactoryService.find(classOf[PlannerFactory], plannerProperties)
.create(
plannerProperties,
executor,
tableConfig,
functionCatalog,
catalogManager)
new StreamTableEnvironmentImpl(
catalogManager,
moduleManager,
functionCatalog,
tableConfig,
executionEnvironment,
planner,
executor,
settings.isStreamingMode
)
}
DataType
定义了逻辑类型，并且对其底层实际物理类型进行暗示。
LogicalType
逻辑类型有点类似标准SQL的数据类型,其子类做了具体的约束。
TableSchema
表结构定义，包含各字段名称和各字段类型
DataStream -> Table
override def fromDataStream[T](dataStream: DataStream[T], fields: Expression*): Table = {
val queryOperation = asQueryOperation(dataStream, Some(fields.toList.asJava))
createTable(queryOperation)
}
ScalaDataStreamQueryOperation
private final DataStream<E> dataStream;
private final int[] fieldIndices;
private final TableSchema tableSchema;
Table
Table类是sql api的核心组件，定义了转换数据的方法如filter、groupBy、join等。使用TableEnvironment类可以把Table转换成DataStream或者DataSet。
private TableImpl(
TableEnvironment tableEnvironment,
QueryOperation operationTree,
OperationTreeBuilder operationTreeBuilder,
LookupCallResolver lookupResolver) {
this.tableEnvironment = tableEnvironment;
this.operationTree = operationTree;
this.operationTreeBuilder = operationTreeBuilder;
this.lookupResolver = lookupResolver;
}
注册表信息
private void createTemporaryView(UnresolvedIdentifier identifier, Table view) {
if (((TableImpl) view).getTableEnvironment() != this) {
throw new TableException(
"Only table API objects that belong to this TableEnvironment can be registered.");
}
CatalogBaseTable tableTable = new QueryOperationCatalogView(view.getQueryOperation());
ObjectIdentifier tableIdentifier = catalogManager.qualifyIdentifier(identifier);
catalogManager.createTemporaryTable(tableTable, tableIdentifier, false);
}
Expression
Expression代表字面量、函数调用或者field引用。
ExpressionVisitor
转换Expression的visitor
IndexedExprToFieldInfo
ExpressionVisitor的子类把Expression解析成FieldInfo
@Override
public FieldInfo visit(UnresolvedReferenceExpression unresolvedReference) {
String fieldName = unresolvedReference.getName();
return new FieldInfo(fieldName, index, fromLegacyInfoToDataType(getTypeAt(unresolvedReference)));
}
应用举例,把Expression转换成FieldInfo:
private static List<FieldInfo> extractFieldInfosFromTupleType(TupleTypeInfoBase<?> inputType, Expression[] exprs) {
boolean isRefByPos = isReferenceByPosition(inputType, exprs);
if (isRefByPos) {
return IntStream.range(0, exprs.length)
.mapToObj(idx -> exprs[idx].accept(new IndexedExprToFieldInfo(inputType, idx)))
.collect(Collectors.toList());
} else {
return extractFieldInfosByNameReference(inputType, exprs);
}
}
FieldInfo
private final String fieldName;
private final int index;
private final DataType type;
Row & RowTypeInfo
代表一行数据，可以包含任意数量的列，并且各列可能包含不同的数据类型.Row不是强类型的所以需要配合RowTypeInfo类获取各列具体的类型.
Row:
/** The array to store actual values. */
private final Object[] fields;
RowTypeInfo:
protected final String[] fieldNames;
protected final TypeInformation<?>[] types;
Table -> DataStream
override def toAppendStream[T: TypeInformation](table: Table): DataStream[T] = {
val returnType = createTypeInformation[T]
val modifyOperation = new OutputConversionModifyOperation(
table.getQueryOperation,
TypeConversions.fromLegacyInfoToDataType(returnType),
OutputConversionModifyOperation.UpdateMode.APPEND)
toDataStream[T](table, modifyOperation)
}
Operation
Parser.parse(sql)的返回结果。
- ModifyOperation (DML)
- QueryOperation (DQL)
- CreateOperation & DropOperation (DDL)
FlinkStreamRuleSets
定义了sql解析优化规则集合,包含把calcite节点转换成flink节点的规则，比如FlinkLogicalTableSourceScan,把flink逻辑节点转换成物理执行节点的规则,比如StreamExecTableSourceScanRule，条件过滤下推的规则PushFilterIntoTableSourceScanRule等.
ConverterRule
/** Converts a relational expression to the target trait(s) of this rule.
*
* <p>Returns null if conversion is not possible. */
public abstract RelNode convert(RelNode rel);
public void onMatch(RelOptRuleCall call) {
RelNode rel = call.rel(0);
if (rel.getTraitSet().contains(inTrait)) {
final RelNode converted = convert(rel);
if (converted != null) {
call.transformTo(converted);
}
}
}
class FlinkLogicalTableSourceScanConverter
extends ConverterRule(
classOf[LogicalTableScan],
Convention.NONE,
FlinkConventions.LOGICAL,
"FlinkLogicalTableSourceScanConverter") {
override def matches(call: RelOptRuleCall): Boolean = {
val scan: TableScan = call.rel(0)
isTableSourceScan(scan)
}
def convert(rel: RelNode): RelNode = {
val scan = rel.asInstanceOf[TableScan]
val table = scan.getTable.asInstanceOf[FlinkRelOptTable]
FlinkLogicalTableSourceScan.create(rel.getCluster, table)
}
}
FlinkLogicalRel
flink RelNode基类不仅包含了RelNode本身可表达的关系依赖逻辑，而且包含了各关系依赖的Flink体系中的额外信息。比如FlinkLogicalTableSourceScan包含了TableSource信息。
FlinkPhysicalRel
物理关系节点基类,其子类同时也会实现ExecNode接口，用于把物理节点转换成Transformation
ExecNode
/**
* Internal method, translates this node into a Flink operator.
*
* @param planner The [[Planner]] of the translated Table.
*/
protected def translateToPlanInternal(planner: E): Transformation[T]
def translateToPlan(planner: E): Transformation[T] = {
if (transformation == null) {
transformation = translateToPlanInternal(planner)
}
transformation
}
调用时序图
代码生成gencode
ExecNode转换成Transformation的过程中部分逻辑会采用动态生成代码的方式实现。动态生成的代码保存在GeneratedClass子类的实例中，会分发到各个TM节点然后由Janino库编译执行。比如聚合查询生成聚合处理函数NamespaceTableAggsHandleFunction的子类。
GeneratedClass
public T newInstance(ClassLoader classLoader, Object... args) {
try {
return (T) compile(classLoader).getConstructors()[0].newInstance(args);
} catch (Exception e) {
throw new RuntimeException(
"Could not instantiate generated class '" + className + "'", e);
}
}
/**
* Compiles the generated code, the compiled class will be cached in the {@link GeneratedClass}.
*/
public Class<T> compile(ClassLoader classLoader) {
if (compiledClass == null) {
// cache the compiled class
compiledClass = CompileUtils.compile(classLoader, className, code);
}
return compiledClass;
}
示例
val sql =
"""
|SELECT
| `string`,
| HOP_START(rowtime, INTERVAL '0.004' SECOND, INTERVAL '0.005' SECOND),
| HOP_ROWTIME(rowtime, INTERVAL '0.004' SECOND, INTERVAL '0.005' SECOND),
| COUNT(1),
| SUM(1),
| COUNT(`int`),
| COUNT(DISTINCT `float`),
| concat_distinct_agg(name)
|FROM T1
|GROUP BY `string`, HOP(rowtime, INTERVAL '0.004' SECOND, INTERVAL '0.005' SECOND)
""".stripMargin
LogicalProject#3
LogicalAggregate#2
LogicalProject#1
LogicalTableScan#0
rel#271:StreamExecSink.STREAM_PHYSICAL.any.None: 0.false.Acc(input=StreamExecCalc#269,name=DataStreamTableSink,fields=string, EXPR$1, EXPR$2, EXPR$3, EXPR$4, EXPR$5, EXPR$6, EXPR$7)
rel#269:StreamExecCalc.STREAM_PHYSICAL.any.None: 0.false.Acc(input=StreamExecGroupWindowAggregate#267,select=string, w$start AS EXPR$1, w$rowtime AS EXPR$2, EXPR$3, EXPR$4, EXPR$5, EXPR$6, EXPR$7)
rel#267:StreamExecGroupWindowAggregate.STREAM_PHYSICAL.any.None: 0.false.Acc(input=StreamExecExchange#265,groupBy=string,window=SlidingGroupWindow('w$, rowtime, 5, 4),properties=w$start, w$end, w$rowtime, w$proctime,select=string, COUNT(*) AS EXPR$3, $SUM0($f2) AS EXPR$4, COUNT(int) AS EXPR$5, COUNT(DISTINCT float) AS EXPR$6, concat_distinct_agg(name) AS EXPR$7, start('w$) AS w$start, end('w$) AS w$end, rowtime('w$) AS w$rowtime, proctime('w$) AS w$proctime)
rel#265:StreamExecExchange.STREAM_PHYSICAL.hash[0]true.None: -1.true.Acc(input=StreamExecCalc#263,distribution=hash[string])
rel#263:StreamExecCalc.STREAM_PHYSICAL.any.None: -1.true.Acc(input=StreamExecDataStreamScan#257,select=string, rowtime, 1 AS $f2, int, float, name)
rel#257:StreamExecDataStreamScan.STREAM_PHYSICAL.any.None: -1.true.Acc(table=[Unregistered_DataStream_2],fields=rowtime, int, double, float, bigdec, string, name)
代码生成:
StreamExecGroupWindowAggregateBase->translateToPlanInternal
StreamExecGroupWindowAggregateBase ->createAggsHandler
AggsHandlerCodeGenerator->generateNamespaceAggsHandler
new OneInputTransformation
任务提交中会把 OneInputTransformation -> OneInputStreamTask
Task->run
Task->doRun
StreamTask->invoke
StreamTask->openAllOperators
AggregateWindowOperator->open
WindowOperator->compileGeneratedCode
GeneratedNamespaceAggsHandleFunction->newInstance
SimpleCompiler->cook