hivesql 迁移spark3.0 sparksql报错如Cannot safely cast '字段':StringType to IntegerType的问题

一 问题

hivesql可以正常运行，spark3.0运行报错如图

spark3.0配置 查看源码新增一个

  val STORE_ASSIGNMENT_POLICY =
    buildConf("spark.sql.storeAssignmentPolicy")
      .doc("When inserting a value into a column with different data type, Spark will perform " +
        "type coercion. Currently, we support 3 policies for the type coercion rules: ANSI, " +
        "legacy and strict. With ANSI policy, Spark performs the type coercion as per ANSI SQL. " +
        "In practice, the behavior is mostly the same as PostgreSQL. " +
        "It disallows certain unreasonable type conversions such as converting " +
        "`string` to `int` or `double` to `boolean`. " +
        "With legacy policy, Spark allows the type coercion as long as it is a valid `Cast`, " +
        "which is very loose. e.g. converting `string` to `int` or `double` to `boolean` is " +
        "allowed. It is also the only behavior in Spark 2.x and it is compatible with Hive. " +
        "With strict policy, Spark doesn‘t allow any possible precision loss or data truncation " +
        "in type coercion, e.g. converting `double` to `int` or `decimal` to `double` is " +
        "not allowed."
      )
      .stringConf
      .transform(_.toUpperCase(Locale.ROOT))
      .checkValues(StoreAssignmentPolicy.values.map(_.toString))
      .createWithDefault(StoreAssignmentPolicy.ANSI.toString)

看下配置有三种类型

  object StoreAssignmentPolicy extends Enumeration {
    val ANSI, LEGACY, STRICT = Value
  }

对于ANSI策略，Spark根据ANSI SQL执行类型强制。这种行为基本上与PostgreSQL相同

它不允许某些不合理的类型转换，如转换“`string`to`int`或`double` to`boolean`

对于LEGACY策略 Spark允许类型强制，只要它是有效的‘Cast‘ 这也是Spark 2.x中的唯一行为，它与Hive兼容。

对于STRICT策略 Spark不允许任何可能的精度损失或数据截断

所以我们增加配置

spark.sql.storeAssignmentPolicy=LEGACY

之后能正常运行

hivesql 迁移spark3.0 sparksql报错如Cannot safely cast '字段':StringType to IntegerType的问题

原文地址：https://www.cnblogs.com/songchaolin/p/12098618.html