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Copy file name to clipboardExpand all lines: articles/hdinsight-aks/flink/hive-dialect-flink.md
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title: Hive dialect in Apache Flink® clusters on HDInsight on AKS
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description: how to use Hive dialect in Apache Flink® clusters on HDInsight on AKS
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description: How to use Hive dialect in Apache Flink® clusters on HDInsight on AKS.
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ms.service: hdinsight-aks
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ms.topic: how-to
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ms.date: 10/27/2023
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ms.date: 04/17/2024
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# Hive dialect in Apache Flink® clusters on HDInsight on AKS
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## Introduction
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The user cannot change the default `flink` dialect to hive dialect for their usage on HDInsight on AKS clusters. All the SQL operations fail once changed to hive dialect with the following error.
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The user can't change the default `flink` dialect to hive dialect for their usage on HDInsight on AKS clusters. All the SQL operations fail once changed to hive dialect with the following error.
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```Caused by:
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*java.lang.ClassCastException: class jdk.internal.loader.ClassLoaders$AppClassLoader cannot be cast to class java.net.URLClassLoader*
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*java.lang.ClassCastException: class jdk.internal.loader.ClassLoaders$AppClassLoader can't be cast to class java.net.URLClassLoader*
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```
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The reason for this issue arises due to an open [Hive Jira](https://issues.apache.org/jira/browse/HIVE-21584). Currently, Hive assumes that the system class loader is an instance of URLClassLoader. In `Java 11`, this assumption is not the case.
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The reason for this issue arises due to an open [Hive Jira](https://issues.apache.org/jira/browse/HIVE-21584). Currently, Hive assumes that the system class loader is an instance of URLClassLoader. In `Java 11`, this assumption isn't the case.
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## How to use Hive dialect in Flink
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- Here is an overview of [hive-dialect queries](https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/hive-compatibility/hive-dialect/queries/overview/)
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- Here's an overview of [hive-dialect queries](https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/hive-compatibility/hive-dialect/queries/overview/)
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- Executing Hive dialect in Flink without partitioning
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