Hive Column Profiler configuration

In addition to the generic configuration, there are additional parameters for the Hive Column Profiler that can optionally be edited.

Go to Profilers > Configs.
Select Hive Column Profiler.
The Detail page is displayed.
Use the toggle button to enable or disable the profiler.
Select a schedule to run the profiler. This is implemented as a quartz cron expression.
For more information, see Understanding the Cron Expression generator.
Select Last Run Check and set a period if needed.

note

The Last Run Check enables profilers to avoid profiling the same asset on each scheduled run.

If you have scheduled a cron job, for example set to start in about an hour, and have enabled the Last Run Check configuration for two days, this setup ensures that the job scheduler filters out any asset which was already profiled in the last two days.

If the Last Run Check configuration is disabled, assets will be picked up for profiling as per the job cron schedule, honoring the asset filter rules.
Set the sampling configurations. When an asset or table is profiled, instead of scanning the whole table, the profiler sample selects only a subset of records as it finds them.
1. Set the Sample Count: Indicates the number of times a table must be sampled for profiling. A value less than 3 and higher than 30 is not recommended.
2. Set the Sample Factor: Controls the randomization of records. Less value promote better random samples and higher values results in poor samples. A value 0.001 indicates that the data that is retrieved from Hive and a new random number is generated. If the value is less than or equal to the provided proportion (0.001), it will be chosen in the result set. If the value is greater, it is ignored. The accepted values range from 0,001 through 0,5.
3. Set the Sample Records: Indicates the number of records to be retrieved in a given sample. Consider this as LIMIT clause of the SQL query. The accepted values range from 100 through 100000.
Continue with the Pod Configurations and set the Kubernetes job resources:
Pod configurations specify the resources that would be allocated to a pod when the profiler job starts to run. As all profilers are submitted as Kubernetes jobs, you must decide if you want to add or reduce resources to handle workload of various sizes.
- Pod CPU limit: Indicates the maximum number of cores that can be allocated to a Pod. The accepted values range from one through eight.
- Pod CPU Requirements: This is the minimum number of CPUs that will be allocated to a Pod when its provisioned. If the node where a Pod is running has enough resources available, it is possible (and allowed) for a container to use more resource than its request for that resource specifies. However, a container is not allowed to use more than its resource limit. The accepted values range from one through eight.
- Pod Memory limit: Maximum amount of memory can be allocated to a Pod. The accepted value format examples are: The accepted values range from 1 through 256.
- Pod Memory Requirements: This is the minimum amount of RAM that will be allocated to a Pod when it is provisioned. If the node where a Pod is running has enough resources available, it is possible (and allowed) for a container to use more resource than its request for that resource specifies. However, a container is not allowed to use more than its resource limit. The accepted values range from 1 through 256.
In Executor Configurations, update the following:
Executor Configurations are the runtime configuration. These configuration must be changed if you are changing the Pod configurations and when there is a requirement for additional compute power.
- Number of workers: Indicates the number of processes that are used by the distributed computing framework. The accepted values range from one through eight.
- Number of threads per worker: Indicates the number of threads used by each worker to complete the job. The accepted values range from one through eight.
- Worker Memory limit in GB: To avoid over utilization of memory, this parameter forces an upper threshold memory usage for a given worker. For example, if you have a 8 GB Pod and 4 threads, the value of this parameter must be 2 GB. The accepted values range from one through four.
Add Asset Filter Rules as needed to customize the selection and deselection of assets which the profiler profiles.
1. Set your Deny List and Allow-list.
  The profiler will skip profiling assets that meet any criteria in the Deny List and will include assets that meet any criteria in the Allow List.
  1. Select the Deny-list or Allow List tab.
  2. Click Add New to include rules.
  3. Select the key from the drop-down list. You can select from the following:
    - Database name
    - Asset name
    - Asset owner
    - Path to the asset
    - Created date
  4. Select the operator from the drop-down list. Depending on the keys selected, you can select an operator such as equals, contains. For example, you can select the name of assets that contain a particular string.
  5. Enter the value corresponding to the key. For example, you can enter a string as mentioned in the previous example.
  6. Click Done. Once rule is added, you can toggle the state of the new rule to enable it or disable it as needed.
Click Save to apply the configuration changes to the selected profiler.