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This article will explain in detail how fs.defaultFS changes make spark-sql query hive fail. The editor thinks it is very practical, so I share it with you as a reference. I hope you can get something after reading this article.

After we change our hdfs to "can", our namede address is changed, that is, after our fs.defaultFS changes, we need to note that these changes will affect the normal operation of our hive, because our hive has already changed the data storage path of the table when we created the table. It will cause us to report an error when we submit the spark script [execute spark-sql]. As shown in the following figure: the namenode path of the hdfs of "read directly".

Here, we can access our hive metadata table SDS, as shown in the following figure: find it at the unupgraded namenode address, that is, master:9000.

Therefore, we need to modify the stored information in two ways: directly modify the information of the table, use the metatool-updateLocation in the hive belt to execute the command metatool-updateLocation hdfs://bi hdfs://master:9000/ on the node with hive to query whether the metadata information has been changed.

Metatool-listFSRoot at this time, the metadata information of hive has been changed and can be used normally

On "fs.defaultFS changes caused spark-sql query hive failure" this article is shared here, I hope the above content can be of some help to you, so that you can learn more knowledge, if you think the article is good, please share it out for more people to see.

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