问题描述

我想使用 Spark 处理来自 JDBC 源的一些数据.但是首先，我想在JDBC端运行一些查询来过滤列和连接表，而不是从JDBC读取原始表，并将查询结果作为表加载到Spark SQL中.

I want to use Spark to process some data from a JDBC source. But to begin with, instead of reading original tables from JDBC, I want to run some queries on the JDBC side to filter columns and join tables, and load the query result as a table in Spark SQL.

以下加载原始 JDBC 表的语法适用于我:

The following syntax to load raw JDBC table works for me:

df_table1 = sqlContext.read.format('jdbc').options(
    url="jdbc:mysql://foo.com:3306",
    dbtable="mydb.table1",
    user="me",
    password="******",
    driver="com.mysql.jdbc.Driver" # mysql JDBC driver 5.1.41
).load() 
df_table1.show() # succeeded

根据 Spark 文档(我使用的是 PySpark 1.6.3):

According to Spark documentation (I'm using PySpark 1.6.3):

dbtable:应该读取的 JDBC 表.请注意，任何有效的可以在 SQL 查询的 FROM 子句中使用.例如，而不是完整的表，您也可以在括号中使用子查询.

dbtable: The JDBC table that should be read. Note that anything that is valid in a FROM clause of a SQL query can be used. For example, instead of a full table you could also use a subquery in parentheses.

所以只是为了实验，我尝试了一些简单的方法:

So just for experiment, I tried something simple like this:

df_table1 = sqlContext.read.format('jdbc').options(
    url="jdbc:mysql://foo.com:3306",
    dbtable="(SELECT * FROM mydb.table1) AS table1",
    user="me",
    password="******",
    driver="com.mysql.jdbc.Driver"
).load() # failed

它抛出了以下异常:

com.mysql.jdbc.exceptions.jdbc4.MySQLSyntaxErrorException: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'table1 WHERE 1=0' at line 1

我还尝试了其他一些语法变体(添加/删除括号、删除as"子句、切换大小写等)，但都没有成功.那么正确的语法是什么?在哪里可以找到更详细的语法文档?此外，错误消息中这个奇怪的WHERE 1 = 0"来自哪里?谢谢！

I also tried a few other variations of the syntax (add / remove parentheses, remove 'as' clause, switch case, etc) without any luck. So what would be the correct syntax? Where can I find more detailed documentation for the syntax? Besides, where does this weird "WHERE 1=0" in error message come from? Thanks!

推荐答案

对于在 Spark SQL 中使用 sql 查询从 JDBC 源读取数据，您可以尝试如下操作:

For reading data from JDBC source using sql query in Spark SQL, you can try something like this:

val df_table1 = sqlContext.read.format("jdbc").options(Map(
    ("url" -> "jdbc:postgresql://localhost:5432/mydb"),
    ("dbtable" -> "(select * from table1) as table1"),
    ("user" -> "me"),
    ("password" -> "******"),
    ("driver" -> "org.postgresql.Driver"))
).load()

我用 PostgreSQL 试过了.可以根据MySQL修改.

I tried it using PostgreSQL. You can modify it according to MySQL.

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