Question

我查看了文档，并说它支持以下连接类型：

要执行的联接类型。默认内心。必须是以下之一：内在，交叉， outer，full，full_outer，left，left_outer，right，right_outer， left_semi，left_anti。

我查看了SQL连接上的StackOverflow answer，前面几个答案没有提到上面的一些连接，例如： left_semi和left_anti。他们在Spark中意味着什么？

Answer 1

这是一个简单的说明性实验：

import org.apache.spark._
import org.apache.spark.sql._
import org.apache.spark.sql.expressions._
import org.apache.spark.sql.functions._

object SparkSandbox extends App {

  case class Row(id: Int, value: String)

  private[this] implicit val spark = SparkSession.builder().master("local[*]").getOrCreate()
  import spark.implicits._
  spark.sparkContext.setLogLevel("ERROR")

  val r1 = Seq(Row(1, "A1"), Row(2, "A2"), Row(3, "A3"), Row(4, "A4")).toDS()
  val r2 = Seq(Row(3, "A3"), Row(4, "A4"), Row(4, "A4_1"), Row(5, "A5"), Row(6, "A6")).toDS()

  val joinTypes = Seq("inner", "outer", "full", "full_outer", "left", "left_outer", "right", "right_outer", "left_semi", "left_anti")

  joinTypes foreach {joinType =>
    println(s"${joinType.toUpperCase()} JOIN")
    r1.join(right = r2, usingColumns = Seq("id"), joinType = joinType).orderBy("id").show()
  }
}

输出

 INNER JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  3|   A3|   A3|
|  4|   A4| A4_1|
|  4|   A4|   A4|
+---+-----+-----+

OUTER JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  1|   A1| null|
|  2|   A2| null|
|  3|   A3|   A3|
|  4|   A4|   A4|
|  4|   A4| A4_1|
|  5| null|   A5|
|  6| null|   A6|
+---+-----+-----+

FULL JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  1|   A1| null|
|  2|   A2| null|
|  3|   A3|   A3|
|  4|   A4| A4_1|
|  4|   A4|   A4|
|  5| null|   A5|
|  6| null|   A6|
+---+-----+-----+

FULL_OUTER JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  1|   A1| null|
|  2|   A2| null|
|  3|   A3|   A3|
|  4|   A4| A4_1|
|  4|   A4|   A4|
|  5| null|   A5|
|  6| null|   A6|
+---+-----+-----+

LEFT JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  1|   A1| null|
|  2|   A2| null|
|  3|   A3|   A3|
|  4|   A4| A4_1|
|  4|   A4|   A4|
+---+-----+-----+

LEFT_OUTER JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  1|   A1| null|
|  2|   A2| null|
|  3|   A3|   A3|
|  4|   A4| A4_1|
|  4|   A4|   A4|
+---+-----+-----+

RIGHT JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  3|   A3|   A3|
|  4|   A4|   A4|
|  4|   A4| A4_1|
|  5| null|   A5|
|  6| null|   A6|
+---+-----+-----+

RIGHT_OUTER JOIN
+---+-----+-----+
| id|value|value|
+---+-----+-----+
|  3|   A3|   A3|
|  4|   A4| A4_1|
|  4|   A4|   A4|
|  5| null|   A5|
|  6| null|   A6|
+---+-----+-----+

LEFT_SEMI JOIN
+---+-----+
| id|value|
+---+-----+
|  3|   A3|
|  4|   A4|
+---+-----+

LEFT_ANTI JOIN
+---+-----+
| id|value|
+---+-----+
|  1|   A1|
|  2|   A2|
+---+-----+

Answer 2

喜欢Pathikrit的例子。这是使用Spark v2和数据框（包括交叉联接）的Java中可能的转换。

package net.jgp.books.sparkInAction.ch12.lab940AllJoins;

import java.util.ArrayList;
import java.util.List;

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructField;
import org.apache.spark.sql.types.StructType;

/**
 * All joins in a single app, inspired by
 * https://stackoverflow.com/questions/45990633/what-are-the-various-join-types-in-spark.
 * 
 * Used in Spark in Action 2e, http://jgp.net/sia
 * 
 * @author jgp
 */
public class AllJoinsApp {

  /**
   * main() is your entry point to the application.
   * 
   * @param args
   */
  public static void main(String[] args) {
    AllJoinsApp app = new AllJoinsApp();
    app.start();
  }

  /**
   * The processing code.
   */
  private void start() {
    // Creates a session on a local master
    SparkSession spark = SparkSession.builder()
        .appName("Processing of invoices")
        .master("local")
        .getOrCreate();

    StructType schema = DataTypes.createStructType(new StructField[] {
        DataTypes.createStructField(
            "id",
            DataTypes.IntegerType,
            false),
        DataTypes.createStructField(
            "value",
            DataTypes.StringType,
            false) });

    List<Row> rows = new ArrayList<Row>();
    rows.add(RowFactory.create(1, "A1"));
    rows.add(RowFactory.create(2, "A2"));
    rows.add(RowFactory.create(3, "A3"));
    rows.add(RowFactory.create(4, "A4"));
    Dataset<Row> dfLeft = spark.createDataFrame(rows, schema);
    dfLeft.show();

    rows = new ArrayList<Row>();
    rows.add(RowFactory.create(3, "A3"));
    rows.add(RowFactory.create(4, "A4"));
    rows.add(RowFactory.create(4, "A4_1"));
    rows.add(RowFactory.create(5, "A5"));
    rows.add(RowFactory.create(6, "A6"));
    Dataset<Row> dfRight = spark.createDataFrame(rows, schema);
    dfRight.show();

    String[] joinTypes = new String[] { 
        "inner", // v2.0.0. default
        "cross", // v2.2.0
        "outer", // v2.0.0
        "full", // v2.1.1
        "full_outer", // v2.1.1
        "left", // v2.1.1
        "left_outer", // v2.0.0
        "right", // v2.1.1
        "right_outer", // v2.0.0
        "left_semi", // v2.0.0, was leftsemi before v2.1.1
        "left_anti" // v2.1.1
        };

    for (String joinType : joinTypes) {
      System.out.println(joinType.toUpperCase() + " JOIN");
      Dataset<Row> df = dfLeft.join(
          dfRight, 
          dfLeft.col("id").equalTo(dfRight.col("id")), 
          joinType);
      df.orderBy(dfLeft.col("id")).show();
    }
  }
}

我将把这个示例放在Spark in Action, 2e的chapter 12 repository中。

Answer 3

System.Diagnostics.Process.GetCurrentProcess().Kill();

Answer 4

支持的联接类型包括：

   inner  
    outer  
     full  
      fullouter  
       full_outer  
        leftouter  
         left  
          left_outer  
           rightouter  
            right  
             right_outer  
              leftsemi  
               left_semi  
                leftanti  
                 left_anti  
                  cross

Answer 5

Left Semi返回在两个表中都找到了连接键的行，但是它仅包含左表中的字段。

Left Anti返回仅在左表中找到连接键的行。

各种连接类型的详细说明： https://www.cloudera.com/documentation/enterprise/latest/topics/impala_joins.html

Spark中的各种连接类型有哪些？

5 个答案: