项目实战从0到1之Spark（7）读写Redis数据

@羲凡——只为了更好的活着

Spark2.0 读写Redis数据(scala)——redis5.0.3

特别强调楼主使用spark2.3.2版本，redis5.0.3版本

1.准备工作

在pom.xml文件中要添加

<dependency>
    <groupId>com.redislabs</groupId>
    <artifactId>spark-redis</artifactId>
    <version>2.3.1-RC1</version>
</dependency>

2.代码

import org.apache.spark.sql.types.{IntegerType,StringType,StructField,StructType}
import org.apache.spark.sql.{SaveMode, SparkSession}

object SparkReadRedis {
  case class Person(name: String, age: Int)
  def main(args: Array[String]): Unit = {
    val spark = SparkSession.builder()
      .appName("SparkReadRedis")
      .master("local[*]")
      .config("spark.redis.host","10.101.12.104")
      .config("spark.redis.port", "6379")
      .config("spark.redis.auth","aaron227") //指定redis密码
      .config("spark.redis.db","0") //指定redis库
      .getOrCreate()
    // 将数据写入到redis中
    val personSeq = Seq(Person("Aaron", 30), Person("Peter", 45))
    val df = spark.createDataFrame(personSeq)
    df.write
      .format("org.apache.spark.sql.redis")
      .option("table", "person")
      .option("key.column", "name")
      .mode(SaveMode.Overwrite)
      .save()

    // 从redis中读取数据————方法一
    val loadedDf = spark.read
      .format("org.apache.spark.sql.redis")
      .option("table", "person")
      .option("key.column", "name")
      .load()
    loadedDf.show(false)

    // 从redis中读取数据————方法二
    spark.sql(
      s"""
         |CREATE TEMPORARY VIEW person
         |(name STRING, age INT,address STRING, salary DOUBLE)
         |USING org.apache.spark.sql.redis
         |OPTIONS (table 'person',key.column "name")""".stripMargin)
    val loadedDf2 = spark.sql(s"SELECT * FROM person")
    loadedDf2.show(false)

    // 从redis中读取数据————方法三
    val loadedDf3 = spark.read
      .format("org.apache.spark.sql.redis")
      .schema(StructType(Array(StructField("id", IntegerType),
        StructField("name", StringType), StructField("age", IntegerType))))
      .option("keys.pattern", "person:*")
      .option("key.column", "name")
      .load()
    loadedDf3.show(false)

    spark.stop()
  }
}

3.结果检验

a. 检查写入是否成功,查询redis结果如下

b. 检查读取是否成功,控制台打印结果展示

+-----+---+
|name |age|
+-----+---+
|Peter|45 |
|Aaron|30 |
+-----+---+

+-----+---+-------+------+
|name |age|address|salary|
+-----+---+-------+------+
|Peter|45 |null   |null  |
|Aaron|30 |null   |null  |
+-----+---+-------+------+

+----+-----+---+
|id  |name |age|
+----+-----+---+
|null|Peter|45 |
|null|Aaron|30 |
+----+-----+---+