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I see that Delta Lake has an OPTIMIZE command and also table properties for Auto Optimize. What are the differences between these and when should I use one over the other?
What about ReOrg delta table https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-reorg-tableDoes it help or make sense to add Re-org then Optimize - Vacuum every week?Reorganize a Delta Lake table by rewriting files to purge ...
from 10.4 LTS version we have low shuffle merge, so merge is more faster. But what about MERGE INTO function that we run in sql notebook of databricks. Is there any performance difference when we use databrciks pyspark ".merge" function vs databricks...
Hi @Roshan RC Thank you for posting your question in our community! We are happy to assist you.To help us provide you with the most accurate information, could you please take a moment to review the responses and select the one that best answers you...
I have a bunch of data frames from different data sources. They are all time series data in order of a column timestamp, which is an int32 Unix timestamp. I can join them together by this and another column join_idx which is basically an integer inde...
@Erik Louie :If the data frames have different time zones, you can use Databricks' timezone conversion function to convert them to a common time zone. You can use the from_utc_timestamp or to_utc_timestampfunction to convert the timestamp column to ...
Hi! I'm optimizing several Tb of partitioned data on ZSTD lvl 9.It surprises me the level of shuffle write, it could make sense because of ZORDER but I want to be sure that I'm not missing something, here is some context: Could I be missing something...
Hi @Alejandro Martinez Thank you for posting your question in our community! We are happy to assist you.To help us provide you with the most accurate information, could you please take a moment to review the responses and select the one that best an...
I have have started getting an error message when running the following optimize command:-deltaTable.optimize().executeCompaction()Error:-java.util.concurrent.ExecutionException: java.lang.IllegalStateException: Number of records changed after Optimi...
@Dean Lovelace :The error message suggests that the number of records in the Delta table changed after the optimize() command was run. The optimize() command is used to improve the performance of Delta tables by removing small files and compacting l...
Optimize and compaction are operations commonly used in Apache Spark for optimizing and improving the performance of data storage and processing. Databricks, which is a cloud-based platform for Apache Spark, provides support for these operations on v...
Trying to optimize delta table with following stats:size: 212,848 blobs, 31,162,417,246,985 bytescommand: OPTIMIZE <table> ZORDER BY (X, Y, Z)In Spark UI I can see all work divided to batches, and each batch start with 400 tasks to collect data. But ...
I am learning how to optimize Spark applications with experiments from Spark UI Simulator. There is experiment #1596 about data skew and in command 2 there is comment about how many partitions will be set as default:// Factor of 8 cores and greater ...
Hi @Bartosz Maciejewski Generally we arrive at the number of shuffle partitions using the following method.Input Size Data - 100 GBIdeal partition target size - 128 MBCores - 8Ideal number of partitions = (100*1028)/128 = 803.25 ~ 804To utiltize the...
Greetings,I have been reading the excellent article from https://docs.databricks.com/security/privacy/gdpr-delta.html?_ga=2.130942095.1400636634.1649068106-1416403472.1644480995&_gac=1.24792648.1647880283.CjwKCAjwxOCRBhA8EiwA0X8hi4Jsx2PulVs_FGMBdByBk...
@Hubert Dudek thanks for the hint, exactly as written in the article VACUUM is required after the GDPR delete operation, however do we need to OPTIMIZE ZSORT again the table or is the ordering maintained?
Hi, have Databricks running on AWS, I'm looking for a way to know when is a good time to run optimize on partitioned tables. Taking into account that it's an expensive process, especially on big tables, how could I know if it's a good time to run it ...
@Alejandro Martinez - If Jose's answer resolved your question, would you be happy to mark his answer as best? That helps other members find the answer more quickly.
I have a table on which I do upsert i.e. MERGE INTO table_name ...After which I run OPTIMIZE table_nameWhich throws an errorjava.util.concurrent.ExecutionException: io.delta.exceptions.ConcurrentDeleteReadException: This transaction attempted to read...
You can try to change isolation level:https://docs.microsoft.com/en-us/azure/databricks/delta/optimizations/isolation-levelIn merge is good to specify all partitions in merge conditions.It can also happen when script is running concurrently.
HI,i have several delta tables on Azure adls gen 2 storage account running databricks runtime 7.3. there are only write/read operation on delta tables and no update/delete.As part of release pipeline, below commands are executed in a new notebook in...
the auto optimize is sufficient, unless you run into performance issues.Then I would trigger an optimize. This will generate files of 1GB (so larger than the standard size of auto optimize). And of course the Z-Order if necessary.The suggestion to ...
For context, I am running Spark on databricks platform and using Delta Tables (s3). Let's assume we a table called table_one. I create a view called view_one using the table and then call view_one. Next, I create another view, called view_two based o...
Hi @John Constantine ,The following notebook url will help you to undertand better the difference between lazy transformations and action in Spark. You will be able to compare the physical query plans and undertand better what is going on when you e...
I have been testing OPTIMIZE a huge set of data (about 775 million rows) and getting mixed results. When I tried on a 'string' column, the query return in 2.5mins and using the same column as 'integer', using the same query, it return 9.7 seconds. Pl...
