DataWorks:ListQualityResultsByEntity

The strength of the monitoring rule. The strength of a monitoring rule indicates the importance of the rule. Valid values:

• 1: the monitoring rule is a strong rule.
• 0: the monitoring rule is a weak rule. You can specify whether a monitoring rule is a strong rule based on your business requirements. If a monitoring rule is a strong rule and the critical threshold is exceeded, a critical alert is reported and tasks that are associated with the rule are blocked from running.

The threshold for a warning alert. The threshold indicates the deviation of the check result from the expected value. You can customize this threshold based on your business requirements.

The field whose data quality is checked based on the monitoring rule. This field is a column in the data source table that is monitored.

The name of the table that is monitored.

The description of the monitoring rule.

The check result of the monitoring rule. Valid values:

• 0: indicates that the data source table is normal.
• 1: indicates that a warning alert is reported.
• 2: indicates that a critical alert is reported.

The name of the monitoring template.

The name of the checker.

The ID of the monitoring rule.

Indicates whether the monitoring is performed based on a fixed value. Valid values:

• true
• false

The comparison operator.

The upper limit of the predicted result. The value of this parameter is automatically generated based on the threshold that you specify.

The monitored partition in the data source table.

The node ID.

The time that was taken to run the monitoring task. Unit: seconds.

The trend of the check result.

The type of the scheduling system. Only CWF scheduling systems are supported.

The data timestamp. In most cases, if the monitored business entity is offline data, the value is one day before the monitoring is performed.

The check result. The value of this parameter is the same as the value of the CheckResultStatus parameter. Valid values:

• 0: indicates that the data source table is normal.
• 1: indicates that a warning alert is reported.
• 2: indicates that a critical alert is reported.

The string of the check result.

The partition filter expression.

The check type. Valid values:

• 0: indicates that the monitoring is performed based on a fixed value.
• 1: indicates that the monitoring is performed based on a non-fixed value.
• 2: indicates that the monitoring is performed based on a dynamic threshold.

The name of the compute engine or data source for which data quality is monitored.

The time when the monitoring started.

The scheduling frequency. In most cases, the value of this parameter is YMD. This value indicates year, month, and day.

The threshold for a critical alert. The threshold indicates the deviation of the check result from the expected value. You can specify a value for the threshold based on your business requirements. If a monitoring rule is a strong rule and the critical threshold is exceeded, a critical alert is reported and tasks that are associated with the rule are blocked from running.

Indicates whether the check result is the same as the predicted result. Valid values:

• true
• false

The name of the monitoring rule.

The checker ID.

Indicates whether the monitoring is discrete monitoring. Valid values:

• true
• false

The deadline for querying the check result.

The method used to collect sample data, such as such as avg, count, sum, min, max, count_distinct, user_defined, table_count, table_size, table_dt_load_count, table_dt_refuseload_count, null_value, null_value/table_count, (table_count-count_distinct)/table_count, or table_count-count_distinct.

The lower limit of the predicted result. The value of this parameter is automatically generated based on the threshold that you specify.

The ID of the partition filter expression.

The filter condition of the monitoring rule.

The expected value.

The ID of the monitoring template.

The monitoring task ID.

The primary key ID.

The historical sample values.

The current sample value.