Read and Write of Dirty Data of Different Data Sources

During dataset migration, dirty data may be generated due to data type mismatch, incorrect formats, or constraints and conflicts. CDM can record and write dirty data to a specified path for subsequent analysis and processing.

The following table lists the support for read and write of dirty data of different data sources.

**Table 1** Read and write of dirty data of different data sources
Data Source	Read	Write
MySQL	√	√
PostgreSQL	√	√
SQL Server	√	√
SAP HANA	√	√
Oracle	√	√
GBase	√	√
GaussDB	√	√
DWS	√	√
DLI	x	√
MRS Hive and Apache Hive	√	x
MRS Hudi	√	x
MRS ClickHouse and Apache ClickHouse	√	x
Doris	√	√
MRS HBase	√	√
MongoDB	√	√
Redis	√	√
Elasticsearch	√	√
DMS Kafka	x	x
LTS	x	x
Apache RocketMQ	x	x
RestClient	x	x
Apache HDFS	√	x
OBS	√	x
FTP	√	x
SFTP	√	x

Parent topic: Creating a Job in a CDM Cluster

Previous topic: Managing CDM Jobs

Next topic: Viewing Traces

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