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The following is an example: 1 val idCol = jdbcDF.col("id") drop drop is used to delete a specified field. Specify a field you need to delete (only one field can be deleted at a time), the DataFrame object that does not contain the field is returned.
As a source, the upsert-kafka connector produces a changelog stream, where each data record represents an update or delete event.
In this case, it is advised to delete the current data connection and create a data catalog again. Creating a Database You can create a database on either the Data Management page or the SQL Editor page.
By setting the lifecycle of a table, you can better manage a large number of tables, automatically delete data tables that are no longer used for a long time, and simplify the process of reclaiming data tables.
Caveats The JDBC sink operates in upsert mode for exchanging UPDATE/DELETE messages with the external system if a primary key is defined on the DDL, otherwise, it operates in append mode and does not support to consume UPDATE/DELETE messages.
If you set this parameter to true, DLI does not delete partitions before overwrite starts. spark.sql.files.maxPartitionBytes 134217728 Maximum number of bytes to be packed into a single partition when a file is read. spark.sql.badRecordsPath - Path of bad records. spark.sql.legacy.correlated.scalar.query.enabled
Job types include DDL, DCL, IMPORT, EXPORT, QUERY, INSERT, DATA_MIGRATION, UPDATE, DELETE, RESTART_QUEUE, and SCALE_QUEUE. To query all types of jobs, enter ALL. job-status No String Status of the job to be queried. job-id No String ID of the job to be queried.
You can use the API to batch delete Flink jobs in any status.
Version dynamic_0001 Scan files number Maximum number of files to be scanned Dynamic Spark HetuEngine Info Block Value range: 1–2000000 Default value: 200000 Yes N/A Spark 3.3.1 dynamic_0002 Scan partitions number Maximum number of partitions involved in the operations (select, delete
"Effect": "Allow", "Action": [ "dli:table:showPartitions", "dli:table:alterTableAddPartition", "dli:table:alterTableAddColumns", "dli:table:alterTableRenamePartition", "dli:table:delete
CURRENT_TIMESTAMP, CURRENT_TRANSFORM_GROUP_FOR_TYPE, CURRENT_USER, CURSOR, CURSOR_NAME, CYCLE, DATA, DATABASE, DATE, DATETIME_INTERVAL_CODE, DATETIME_INTERVAL_PRECISION, DAY, DEALLOCATE, DEC, DECADE, DECIMAL, DECLARE, DEFAULT, DEFAULTS, DEFERRABLE, DEFERRED, DEFINED, DEFINER, DEGREE, DELETE
Change the JDK version in the sample code to a version earlier than 8u_242 or delete the renew_lifetime = 0m configuration item from the krb5.conf configuration file. Set the port to the sasl.port configured in the Kafka service configuration.
You need to delete the indentations or spaces after the backslashes (\).
parameters Parameter Description Example Value Name Enter a unique link name. mysqllink Database Server IP address or domain name of the MySQL database - Port Port number of the MySQL database 3306 Database Name Name of the MySQL database sqoop Username User who has the read, write, and delete
in MySQL. insert into cdc_order values ('202103241000000001','webShop','2021-03-24 10:00:00','100.00','100.00','2021-03-24 10:02:03','0001','Alice','330106'), ('202103241606060001','appShop','2021-03-24 16:06:06','200.00','180.00','2021-03-24 16:10:06','0001','Alice','330106'); delete
As a source, the upsert-kafka connector produces a changelog stream, where each data record represents an update or delete event.
The auto.purge parameter can be used to specify whether to clear related data when data removal operations (such as DROP, DELETE, INSERT OVERWRITE, and TRUNCATE TABLE) are performed. If it is set to true, metadata and data files are cleared.
Insert data. 1 sparkSession.sql("insert into css_table values(13, 'John'),(22, 'Bob')") Query data. 1 2 val dataFrame = sparkSession.sql("select * from css_table") dataFrame.show() Before data is inserted: Response: Delete the datasource connection table. 1 sparkSession.sql("drop
You can add, delete, modify, and query metadata to facilitate data governance and analysis. Data security and permission management: Permissions on data catalogs, databases, and tables can be managed.
If a primary key is defined, the Elasticsearch sink works in upsert mode, which can consume queries containing UPDATE and DELETE messages. If a primary key is not defined, the Elasticsearch sink works in append mode which can only consume queries containing INSERT messages.
