- 18532 Views
- 1 replies
- 2 kudos
Resolved! How do I change the log level in Databricks?
How can I change the log level of the Spark Driver and executor process?
- 18532 Views
- 1 replies
- 2 kudos
- 2 kudos
Change the log level of Driver:%scala spark.sparkContext.setLogLevel("DEBUG") spark.sparkContext.setLogLevel("INFO")Change the log level of a particular package in Driver logs:%scala org.apache.log4j.Logger.getLogger("shaded.databricks.v201809...
- 2 kudos
- 2323 Views
- 1 replies
- 0 kudos
Resolved! I do not have any Spark jobs running, but my cluster is not getting auto-terminated.
The cluster is Idle and there are no Spark jobs running on the Spark UI. Still I see my cluster is active and not getting terminated.
- 2323 Views
- 1 replies
- 0 kudos
- 0 kudos
Databricks cluster is treated as active if there are any spark or non-Spark operations running on the cluster. Even though there are no Spark jobs running on the cluster, it's possible to have some driver-specific application code running marking th...
- 0 kudos
- 5461 Views
- 1 replies
- 1 kudos
- 5461 Views
- 1 replies
- 1 kudos
- 1 kudos
Disclaimer: This code snippet uses an internal API. It's not recommended to use internal API's in your application as they are subject to change or discontinuity. %python import requests API_URL = dbutils.notebook.entry_point.getDbutils().notebook(...
- 1 kudos
- 1416 Views
- 1 replies
- 1 kudos
- 1416 Views
- 1 replies
- 1 kudos
- 1 kudos
No, currently it's not configurable. Synching of notebooks to Git repositories is configurable and can be turned off at the workspace level.
- 1 kudos
- 3257 Views
- 1 replies
- 0 kudos
Resolved! Why do I see my job marked as failed on the Databricks Jobs UI, even though it completed the operations in the application
I have a jar job running migrated from EMR to Databricks. The job runs as expected and completes all the operations in the application. However the job run is marked as failed on the Databricks Jobs UI.
- 3257 Views
- 1 replies
- 0 kudos
- 0 kudos
Usage of spark.stop(), sc.stop() , System.exit() in your application can cause this behavior. Databricks manages the context shutdown on its own. Forcefully closing it can cause this abrupt behavior.
- 0 kudos
- 1551 Views
- 1 replies
- 2 kudos
Few things you should not do in Databricks!
Few things you should not do in Databricks!
- 1551 Views
- 1 replies
- 2 kudos
- 2 kudos
Compared to OSS Spark, these are few things the users don't have to worry about when running the same job on Databricks. Memory management: Databricks use an internal formula to allocate the Driver and executor heap based on the size of the instance....
- 2 kudos
- 3343 Views
- 1 replies
- 0 kudos
- 3343 Views
- 1 replies
- 0 kudos
- 0 kudos
Although not a hard limit, it's recommended to keep the number of cells in the notebook less than 100 for better UI experience as well as code readability. Having a really large block of code in a cell defeats the purpose of notebook execution and al...
- 0 kudos
- 22572 Views
- 1 replies
- 0 kudos
Resolved! Can I download files from DBFS to my local machine? I see only the Upload option in the Web UI.
- 22572 Views
- 1 replies
- 0 kudos
- 0 kudos
Yes, it's possible to download files from DBFS. To download the filesFiles stored in /FileStore are accessible in your web browser at https://<databricks-instance-name>.cloud.databricks.com/files/. For example, the file you stored in /FileStore/my-da...
- 0 kudos
- 1835 Views
- 2 replies
- 0 kudos
What is the best way to convert a very large parquet table to delta ? possibly without downtime!
What is the best way to convert a very large parquet table to delta ? possibly without downtime!
- 1835 Views
- 2 replies
- 0 kudos
- 0 kudos
I vouch for Sajith's answer. The main advantage with "CONVERT TO DELTA" is that operations are metadata centric which means we are not reading the full data for the conversion. For any other file format conversion, it's necessary to read the data com...
- 0 kudos
- 1938 Views
- 2 replies
- 0 kudos
Why should I move to Auto-loader?
I have a streaming workload using the S3-SQS Connector. The streaming job is running fine within the SLA. Should I migrate my job to use the auto-loader? If Yes, what are the benefits? who should migrate and who should not?
- 1938 Views
- 2 replies
- 0 kudos
- 0 kudos
That makes sense @Anand Ladda​ ! One major improvement that will have a direct impact on the performance is the architectural difference. S3-SQS uses an internal implementation of the Delta table to store the checkpoint details about the source files...
- 0 kudos
- 3373 Views
- 1 replies
- 0 kudos
- 3373 Views
- 1 replies
- 0 kudos
- 0 kudos
Stats collected on a Delta column are either using for Partitioning Pruning, Data Skipping. See here - https://docs.databricks.com/delta/optimizations/file-mgmt.html#delta-data-skipping for detailsIn additional stats are also used for Metadata only q...
- 0 kudos
- 1768 Views
- 0 replies
- 0 kudos
What are the recommendations around collecting stats on long strings in a Delta Table
It is best to avoid collecting stats on long strings. You typically want to collect stats on column that are used in filter, where clauses, joins and on which you tend to performance aggregations - typically numerical valuesYou can avoid collecting s...
- 1768 Views
- 0 replies
- 0 kudos
- 1840 Views
- 2 replies
- 0 kudos
Delta Optimistic Transactions Resolution and Exceptions
What is the best way to deal with concurrent exceptions in Delta when you have multiple writers on the same delta table ?
- 1840 Views
- 2 replies
- 0 kudos
- 0 kudos
While you can try-catch-retry , it would be expensive to retry as the underlying table snapshot would have changed. So the best approach is to avoid conflicts using partitioning and disjoint command conditions as much as possible.
- 0 kudos
- 6443 Views
- 1 replies
- 0 kudos
- 6443 Views
- 1 replies
- 0 kudos
- 0 kudos
by default a delta table has stats collected on the first 32 columns. This setting can be configured using the following.set spark.databricks.delta.properties.defaults.dataSkippingNumIndexedCols = 3However there's a time trade-off to having a large n...
- 0 kudos
- 1296 Views
- 1 replies
- 0 kudos
- 1296 Views
- 1 replies
- 0 kudos
- 0 kudos
Its typically a good idea to run optimize aligned with the frequency of updates to the Delta Table. However you also don't want to over do as there's a cost/performance trade-off. Unless there are very frequent updates to the table that can cause sma...
- 0 kudos
| User | Count |
|---|---|
| 1615 | |
| 780 | |
| 349 | |
| 287 | |
| 275 |
