在(Py)Spark中读取JDBC源时出现不受支持的数组错误? [英] Unsupported Array error when reading JDBC source in (Py)Spark?

问题描述

尝试将postgreSQL DB转换为Dataframe.以下是我的代码:

Trying to convert postgreSQL DB to Dataframe . Following is my code:

from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName("Connect to DB") \
    .getOrCreate()

jdbcUrl = "jdbc:postgresql://XXXXXX" 
connectionProperties = {
  "user" : " ",
  "password" : " ",
  "driver" : "org.postgresql.Driver"
}

query = "(SELECT table_name FROM information_schema.tables) XXX"
df = spark.read.jdbc(url=jdbcUrl, table=query, properties=connectionProperties)

table_name_list = df.select("table_name").rdd.flatMap(lambda x: x).collect() 
    for table_name in table_name_list:
          df2 = spark.read.jdbc(url=jdbcUrl, table=table_name, properties=connectionProperties)

我遇到的错误:

java.sql.SQLException:为表名生成df2时，不支持的类型ARRAY

java.sql.SQLException: Unsupported type ARRAY on generating df2 for table name

如果我对表名进行硬编码，则不会得到相同的错误

If I hard code table name value , I do not get the same error

df2 = spark.read.jdbc(jdbcUrl,"conditions",properties=connectionProperties) 

我检查了table_name类型，它是String，这是正确的方法吗?

I checked table_name type and it is String , is this the correct approach ?

推荐答案

我猜您不希望属于postgres内部工作的表名，例如 pg_type ， pg_policies 等，其架构的类型为 pg_catalog 的类型会导致

I guess you don't want the table names that belong to internal working of postgres such as pg_type, pg_policies etc whose schema are of type pg_catalog that causes the error

py4j.protocol.Py4JJavaError:调用o34.jdbc时发生错误.:java.sql.SQLException:不支持的ARRAY类型

py4j.protocol.Py4JJavaError: An error occurred while calling o34.jdbc. : java.sql.SQLException: Unsupported type ARRAY

当您尝试将它们阅读为

spark.read.jdbc(url=jdbcUrl, table='pg_type', properties=connectionProperties)

并且有诸如 applicable_roles ， view_table_usage 之类的表，这些表的模式为导致

and there are tables such as applicable_roles, view_table_usage etc whose schema are of type information_schema that causes

py4j.protocol.Py4JJavaError:调用o34.jdbc时发生错误.:org.postgresql.util.PSQLException:错误:关系"view_table_usage"不存在

py4j.protocol.Py4JJavaError: An error occurred while calling o34.jdbc. : org.postgresql.util.PSQLException: ERROR: relation "view_table_usage" does not exist

当您尝试将它们阅读为

spark.read.jdbc(url=jdbcUrl, table='view_table_usage', properties=connectionProperties)

可以使用上述jdbc命令将模式类型为公共的表读入表中.

The tables whose schema types are public can be read into tables using above jdbc commands.

我检查了table_name类型，它是String，这是正确的方法吗?

I checked table_name type and it is String , is this the correct approach ?

因此，您需要过滤掉这些表名，并将逻辑应用为

So you need to filter out those table names and apply your logic as

from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName("Connect to DB") \
    .getOrCreate()

jdbcUrl = "jdbc:postgresql://hostname:post/" 
connectionProperties = {
  "user" : " ",
  "password" : " ",
  "driver" : "org.postgresql.Driver"
}

query = "information_schema.tables"
df = spark.read.jdbc(url=jdbcUrl, table=query, properties=connectionProperties)

table_name_list = df.filter((df["table_schema"] != 'pg_catalog') & (df["table_schema"] != 'information_schema')).select("table_name").rdd.flatMap(lambda x: x).collect() 
    for table_name in table_name_list:
          df2 = spark.read.jdbc(url=jdbcUrl, table=table_name, properties=connectionProperties)

应该可以

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