spark通过jdbc访问postgresql数据库

蔚落 2022-08-18 05:40 525阅读 0赞

**1.首先要有可用的jdbc**

[hadoop@db1 bin]$ locate jdbc|grep postgres
    /mnt/hd01/www/html/deltasql/clients/java/dbredactor/lib/postgresql-8.2-507.jdbc4.jar
    /usr/lib/ruby/gems/1.8/gems/railties-3.2.13/lib/rails/generators/rails/app/templates/config/databases/jdbcpostgresql.yml
    /usr/src/postgis-2.0.0/java/jdbc/src/org/postgresql
    /usr/src/postgis-2.0.0/java/jdbc/src/org/postgresql/driverconfig.properties
    /usr/src/postgis-2.0.0/java/jdbc/stubs/org/postgresql
    /usr/src/postgis-2.0.0/java/jdbc/stubs/org/postgresql/Connection.java
    /usr/src/postgis-2.0.0/java/jdbc/stubs/org/postgresql/PGConnection.java
    /usr/src/postgis-2.1.0/java/jdbc/src/org/postgresql
    /usr/src/postgis-2.1.0/java/jdbc/src/org/postgresql/driverconfig.properties
    /usr/src/postgis-2.1.0/java/jdbc/stubs/org/postgresql
    /usr/src/postgis-2.1.0/java/jdbc/stubs/org/postgresql/Connection.java
    /usr/src/postgis-2.1.0/java/jdbc/stubs/org/postgresql/PGConnection.java
    没有合适的，就在管网下载：https://jdbc.postgresql.org/download/postgresql-9.4-1205.jdbc4.jar

**2.把下载好的jar文件放在$SPARK\_HOME/lib下面  
3.启动sparck shell**

[hadoop@db1 bin]$ SPARK_CLASSPATH=$SPARK_HOME/lib/postgresql-9.4-1205.jdbc4.jar $SPARK_HOME/bin/spark-shell
    .
    .
    .
    Please instead use:
     - ./spark-submit with --driver-class-path to augment the driver classpath
     - spark.executor.extraClassPath to augment the executor classpath
    
    15/11/04 17:53:05 WARN SparkConf: Setting 'spark.executor.extraClassPath' to '/usr/src/data-integration/lib/postgresql-9.3-1102-jdbc4.jar' as a work-around.
    15/11/04 17:53:05 WARN SparkConf: Setting 'spark.driver.extraClassPath' to '/usr/src/data-integration/lib/postgresql-9.3-1102-jdbc4.jar' as a work-around.
    15/11/04 17:53:06 WARN Utils: Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
    15/11/04 17:53:07 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
    Spark context available as sc.
    15/11/04 17:53:09 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
    15/11/04 17:53:09 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
    15/11/04 17:53:25 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
    15/11/04 17:53:25 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
    15/11/04 17:53:28 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    15/11/04 17:53:29 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
    15/11/04 17:53:29 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
    SQL context available as sqlContext.

**4.创建DataFrame对象**

scala> val df = sqlContext.load("jdbc", Map("url" -> "jdbc:postgresql://localhost:5434/cd03?user=cd03&password=cd03", "dbtable" -> "test_trans"))
    warning: there were 1 deprecation warning(s); re-run with -deprecation for details
    df: org.apache.spark.sql.DataFrame = [trans_date: string, trans_prd: int, trans_cust: int]
    标准格式：
    val jdbcDF = sqlContext.read.format("jdbc").options( 
      Map("url" -> "jdbc:postgresql:dbserver",
      "dbtable" -> "schema.tablename")).load()

**5.查看schema**

scala> df.printSchema()
    root
     |-- trans_date: string (nullable = true)
     |-- trans_prd: integer (nullable = true)
     |-- trans_cust: integer (nullable = true)

**6.简单计算**

scala> df.filter(df("trans_cust")>9999999).select("trans_date","trans_prd").show
    +----------+---------+
    |trans_date|trans_prd|
    +----------+---------+
    | 2015-5-20|     2007|
    | 2015-7-24|     5638|
    | 2015-5-19|     8182|
    | 2015-2-24|    11391|
    | 2015-8-13|    17341|
    | 2015-2-22|    10996|
    | 2015-1-17|    15284|
    |  2015-1-8|    16090|
    | 2015-1-25|    13528|
    | 2015-1-17|     9498|
    | 2015-9-25|     7235|
    | 2015-8-19|     4084|
    | 2015-4-24|    16637|
    | 2015-5-27|    13829|
    | 2015-0-13|    13956|
    | 2015-3-19|    11974|
    | 2015-10-5|     1185|
    | 2015-3-28|     9412|
    | 2015-6-13|    15203|
    | 2015-2-14|    10087|
    +----------+---------+
    only showing top 20 rows