- 1868 Views
- 1 replies
- 0 kudos
- 1868 Views
- 1 replies
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While using MERGE INTO statement, if the source data that will be merged into the target delta table is small enough to be fit into memory of the worker nodes, then it makes sense to broadcast the source data. By doing so, the execution can avoid the...
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- 4708 Views
- 1 replies
- 0 kudos
Resolved! Can Spark JDBC create duplicate records
Is it transaction safe?Does it ensure atomicity
- 4708 Views
- 1 replies
- 0 kudos
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Atomicity is ensured at a task level and not at a stage level. For any reason, if the stage is getting retried, the tasks which already completed the write operation will re-run and cause duplicate records. This is expected by design. When Apache Spa...
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- 1273 Views
- 0 replies
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Email Notifications
Do customers need to allow-list the control plane IP ranges to get email notifications about jobs?
- 1273 Views
- 0 replies
- 0 kudos
- 5888 Views
- 1 replies
- 1 kudos
Resolved! What is the best practice of deleting the complete data from Delta table
I have a use case where I need to delete the data completely and load new data to the existing Delta table.
- 5888 Views
- 1 replies
- 1 kudos
- 1 kudos
It's recommended to use the overwrite option. Overwrite the table data and run a VACUUM command. To Delete the data from a Managed Delta table, the DROP TABLE command can be used. If it's an external table, then run a DELETE query on the table and th...
- 1 kudos
- 3080 Views
- 1 replies
- 0 kudos
Resolved! Cluster Log Partitioning
Customer wants to understand our strategy for breaking cluster logs into different partitions and files. They want to be able to ingest these logs into a tool that needs to understand this. They have indicated that the logs used to all be in one file...
- 3080 Views
- 1 replies
- 0 kudos
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Log files are rolled over by time/size criteria.
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- 1057 Views
- 0 replies
- 0 kudos
docs.databricks.com
Best practices for Databricks pools — Databricks DocumentationLearn best practices for configuring and using Databricks pools.https://docs.databricks.com/clusters/instance-pools/pool-best-practices.htmlBest practices for Azure Databricks pools - Azur...
- 1057 Views
- 0 replies
- 0 kudos
- 2635 Views
- 1 replies
- 0 kudos
- 2635 Views
- 1 replies
- 0 kudos
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Pre-emption is by default turned on Databricks cluster. Turning on or turning off pre-emption would make more sense on a high concurrency cluster. Pre-emption ensures that the job starting for resources gets a fair share of the resource available on ...
- 0 kudos
- 3009 Views
- 1 replies
- 0 kudos
Resolved! How to uninstall libraries that are set to auto-install on all cluster - using REST API
I have a bunch of libraries that I want to uninstall. All of them are marked as auto-install.
- 3009 Views
- 1 replies
- 0 kudos
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1) Find the corresponding library definition from an existing cluster using "libraries/cluster-status?cluster_id=<cluster_id>".$ curl -X GET 'https://cust-success.cloud.databricks.com/api/2.0/libraries/cluster-status?cluster_id=1226-232931-cuffs129' ...
- 0 kudos
- 3267 Views
- 1 replies
- 1 kudos
Resolved! Saving Files Location
If someone saves a flat file from a cell without specifying any location, where does it save?
- 3267 Views
- 1 replies
- 1 kudos
- 1 kudos
In this case they are writing to a directory on the driver.
- 1 kudos
- 3803 Views
- 1 replies
- 0 kudos
Resolved! Super slow SQL queries on an HC cluster
I have a high concurrency cluster where multiple users are running. However, I see the queries are running very slow. I did debug the logs and see more time is spent on the Spark driver. on the Spark UI, I do not see slowness.
- 3803 Views
- 1 replies
- 0 kudos
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It's possible the connectivity to hive metastore is causing the delay here. When there is a high degree of concurrency and contention for metastore access. Interactive clusters in DBR are configured to use up to 5 (spark.databricks.hive.metastore.cli...
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- 1306 Views
- 1 replies
- 0 kudos
- 1306 Views
- 1 replies
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You could follow the steps in this article to set up your deployment in a HIPAA-compliant manner.
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- 1405 Views
- 1 replies
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Resolved! versioning of delta table while writing from a structured streaming job
Does writing to a Delta table create a versioning for every micro-batch of stream
- 1405 Views
- 1 replies
- 0 kudos
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Yes it is correct - Every commits to the delta create a version so definitely each micro batch create a version More Info -: https://databricks.com/blog/2019/02/04/introducing-delta-time-travel-for-large-scale-data-lakes.html
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- 2650 Views
- 1 replies
- 1 kudos
spark data frame parquet vs delta : rows Doesn't match
I have data written in Delta on ADLS. As I understand the delta also internal file in parquet format but when Iread the file in different format I got different record countspark.read.parquet() or spark.read.format('delta').load()df = spark.read.for...
- 2650 Views
- 1 replies
- 1 kudos
- 1 kudos
I think you have written in delta twice using overwrite mode .But Delta is versioned data format - when you use overwrite, it doesn't delete previous data, it just writes new files, and don't delete files immediately - they are just marked as delete...
- 1 kudos
- 10957 Views
- 3 replies
- 1 kudos
- 10957 Views
- 3 replies
- 1 kudos
- 1 kudos
Databricks does not charge DBUs while instances are idle in the pool. Instance provider billing does apply.Please refer here for more information - https://docs.databricks.com/clusters/instance-pools/index.html
- 1 kudos
- 5443 Views
- 1 replies
- 0 kudos
Resolved! Best ways to copy the parquet files in the staging directory to the Delta table
I have some parquet data in a temporary directory. Can I copy them into the delta table directly, what are the best options.
- 5443 Views
- 1 replies
- 0 kudos
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The easiest solution is to use the COPY INTO command. The COPY INTO command ensures idempotency, so even if the operation fails there are no data inconsistencies. COPY INTO command utilizes the resources on the Spark cluster hence completes faster. h...
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