Spark delta lake vacuum. It works well but takes hours on huge databases.

Spark delta lake vacuum vacuum. Jan 10, 2025 · Vacuuming Jobs One of the most effective ways to manage historical data in Delta Lake is through vacuuming. This is causing our storage constantly increasing. That retention threshold can be speci Feb 8, 2025 · Fix: Enable Delta Lake retries for consistency issues: spark. With deletion vectors enabled for the table, DELETE, UPDATE, and MERGE operations use deletion vectors to mark existing rows as removed or changed without May 17, 2022 · I created a simple synapse delta lake table via: CREATE TABLE IF NOT EXISTS db1. Feb 21, 2024 · Dive into the world of Delta Lake and discover the powerful capabilities of History, Time Travel, and Vacuum. Differences between Delta Lake and Parquet on Apache Spark Delta May 3, 2024 · In this article, we will explain how the OPTIMIZE and VACUUM commands can assist in maintaining the tables in the Microsoft Fabric Lakehouse. Delta Lake doesn’t need a special disk layout for performance optimizations as Hive does. vacuum(0) During the compaction or vacuum you may get an exception in the running Spark streaming or batch job which can terminate your job. write command pattern. At a moment, I have 43 records available in the delta table in Azure synapse, I did use compaction logic as below, my assumption is, as the data size is less, spark… Feb 5, 2025 · Mastering CDC in Delta Tables: A Use-case in Spark Non-members can access the full article through this Link. read. x, Synapse Spark, Fabric Spark Runtime 1. Add a Z-order index. gc prints out the following message to standard output (with the dirCounts): Jul 4, 2023 · For testing, I want to erase the history of the table with the VACUUM command. Keep your data running smoothly! Mar 25, 2025 · Modern data pipelines are increasingly adopting streaming paradigms, but handling deletes in streaming pipelines is far from trivial. its purpose, risks, and how to use it wisely in modern data pipelines. session. Compaction reads in the referenced files and writes your new partitions back to the table, unreferencing the existing files. format('delta'). Whichever Apr 3, 2025 · Do not use Spark caching with Delta Lake Databricks does not recommend that you use Spark caching for the following reasons: You lose any data skipping that can come from additional filters added on top of the cached DataFrame. You’ll also learn about how the PySpark errorifexists and ignore save mode write operations are implemented with Delta The Delta logs folder plays a critical role in maintaining the integrity and functionality of Delta Lake. The Vacuum command removes the previous versions of Delta Lake files and retains data history up to a specified period. tbl1 ( id INT NOT NULL, name STRING NOT NULL ) USING DELTA I've merged rows of data into it multiple times such that Nov 28, 2022 · We have one project requirement where we have to store only the 14 days history for delta tables. You can use Delta Lake clones to perform data migration and archiving, to reproduce production workflows and to safely share data with external parties. Using Delta Lake with S3 is a great way to make your queries on cloud objects faster by avoiding expensive file listing operations. Create a key named --conf for your AWS Glue job, and set it to the following value. count() > 15000000 df = spark. Apart from the versions, Delta Lake also stores a transaction log to keep track of all the commits made to the table or blob store directory to provide ACID transactions. However, these warehouses struggled when confronted with the deluge of unstructured and semi-structured data, revealing their limitations. See the vacuum documentation for more details on the vacuum command and additional considerations for advanced use cases. Delta Lake 3. x or lower (Databricks Runtime 12. If an OPTIMIZE or VACUUM statement is ran against the Delta table, new files are added/subtract Concisely, Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. set("spark. OPTIMIZE operations will be faster as it will operate on fewer files. gc deletes the untracked files and empty directories (with parallel delete enabled flag based on spark. The default retention We are pleased to announce the release of Delta Lake 3. Without it, your data lake would get cluttered, slowing down queries and bloating storage costs. Each user performs only one action per day, for a total of 10 days. There is no lock-in when you use Delta Lake - you can convert to Parquet tables. However, somehow it is not working and I don't understand why. 0 (in a Glue 4. The key features of this release are: Delta Connect adds Spark Connect support to Scala and Python APIs of Delta Lake for Apache Spark. In this blog, we’ll explore how to handle deletes effectively using Delta Lake and Spark Structured Streaming, with a focus on real-world use cases like GDPR. For more information, see Using job parameters in AWS Glue jobs. 1 (or greater) instance (on Databricks, try Aug 20, 2019 · Learn what the Delta Lake transaction log is, how it works at the file level, and how it enables ACID transactions on Delta Lake. It works well but takes hours on huge databases. You can create DeltaTable instances using the path of the Delta table. Apr 26, 2023 · The right way to do Retention & Vacuuming in Databricks Delta Lake is a data lake technology built on top of Apache Spark that provides ACID transactions and other advanced features to manage big … Vacuum inventory support Delta Lake 3. Discover how data compaction, Z-ordering, file size optimization, and more can significantly enhance the performance and efficiency of your data operations. Over time, as data gets updated or deleted, stale files Delta lake provides a vacuum command that deletes older versions of the data (any data that's older than the specified retention period). SparkSession, jdt: JavaObject) ¶ Main class for programmatically interacting with Delta tables. tables. Display table history. So without running 'vacuum' operation, you can time travel infinitely as all data would be available. For many Delta Lake operations on tables, you enable integration with Apache Spark DataSourceV2 and Catalog APIs (since 3. This blog post explains how to use the vacuum command and situations where it is applicable. Read from a table. When deletion vectors are enabled, the delete operations run even faster. Feb 10, 2021 · The following graph is generated by re-running the previous SQL query against the new reiterator table. Aug 2, 2021 · I'm using Databricks Autoloader to incrementally stream from a Delta Lake table into a SQL database. Jan 25, 2023 · spark. However, VACUUM failures, slow execution, and accidental data loss can occur if not handled correctly. Dec 31, 2024 · Bug Which Delta project/connector is this regarding? Spark Standalone Flink Kernel PySpark Describe the problem We are using Delta Lake version 2. sql(f"VACUUM delta. It brings ACID (Atomicity, Consistency, Isolation, and Durability) transactions to data lakes Jun 23, 2025 · Optimize large datasets in Databricks with Partitioning, Z-Ordering, Auto Optimize, Delta Lake Vacuum, Caching, and Cost Monitoring for better performance. Optimize a table. Delta Lake adds support for relational semantics for both batch and streaming data operations, and enables the creation of a Lakehouse architecture in which Apache Spark can be used to process and query data in tables that are based on underlying Nov 5, 2025 · What is Delta Lake in Databricks? Delta Lake is the optimized storage layer that provides the foundation for tables in a lakehouse on Databricks. Sep 14, 2023 · Hello, I have a delta table, and I do insert, deletes, and update on the delta table. `<path-to-delta-table>` RETAIN 0 HOURS") Integration with ADF: In your ADF pipeline, use the Databricks Notebook activity to call the notebook you created. Learn the practical steps to May 21, 2023 · Delta tables Read, Write, History check, and vacuum using Python (Without Apache Spark) Databricks recommends removing most explicit legacy Delta configurations from Spark configurations and table properties when upgrading to a new Databricks Runtime version. delta. sql. Delta Lake has a safety check to prevent you from running a dangerous VACUUM command. Jun 25, 2025 · You must choose an interval that is longer than the longest running concurrent transaction and the longest period that any stream can lag behind the most recent update to the table. Query an earlier version of a table. 2 introduces vacuum inventory support, a feature that allows users to specify an inventory table in a VACUUM command. 6 days ago · We used to use regular VACUUM xxx RETAIN nnn HOURS query. 0) by setting configurations when you create a new SparkSession. Use Delta Lake in Azure Databricks Delta Lake is an open source project to build a transactional data storage layer for Spark on top of a data lake. —Ryan Zhu, founding developer of Delta Lake, cocreator of Delta Sharing, Apache Spark PMC member, Delta Lake maintainer The authors of this book fuse deep technical knowledge with pragmatism and clear exposition to allow readers to bring their Spark data lakehouse aspirations to life with the Delta Lake framework. Vacuum unreferenced files. We have Azure data lake storing data in parquet files in delta lake format. Whether you’re building scalable pipelines, optimizing queries, or ensuring data governance, this release is designed to help you achieve more with less effort. Delta Lake uses versioned Parquet files to store your data in your cloud storage. VACUUM command for deletion of old Jul 11, 2020 · I'm writing a lot of data into Databricks Delta lake using the open source version, running on AWS EMR with S3 as storage layer. If you are certain that there are no operations being performed on this table that take longer than the retention interval you plan to specify, you can turn off this safety check by setting the Spark configuration property spark. 1. We introduce a utility that auto detects all Delta Lake files in a Synapse workspace and then auto performs “Optimize” and “Vacuum” operations on those files. enabled to false Using Delta Lake on S3 You can read and write Delta Lake tables from and to AWS S3 cloud object storage. Delta Lake is open source software that extends Parquet data files with a file-based transaction log for ACID transactions and scalable metadata handling. Despite continuous data ingestion, I noticed that there were no changes reflected in the Delta log (`_delta_log`). From what I have read, if a table A has 7 version, version 1 timestamp is 2024- Sep 8, 2025 · Tutorial: Delta Lake This tutorial introduces common Delta Lake operations on Databricks, including the following: Create a table. Optimize your Delta Lake tables Small files can cause slow downstream queries. Aug 7, 2022 · Below example removes all histoical data by setting 0 as number of hours. See full list on learn. We set the retention period to 0. Jun 20, 2025 · Delta Lake has a safety check to prevent you from running a dangerous VACUUM command. Delta Lake lets you build a Lakehouse architecture on top of data lakes. Other powerful features include the unification of streaming and batch data Feb 12, 2024 · Delta Lake Database/Schema Maintenance Part-1 In this blog post, I am going to walk you through the journey of delta table maintenance. Jun 13, 2024 · Delta Lake, a storage layer on top of Apache Spark, provides reliable data lakes with ACID transactions and scalable metadata handling. Specify delta as a value for the --datalake-formats job parameter. I've tried with another table with more versions and It works as you say. 1), liquid clustering is not yet available and therefore Z-Order clustering is the closest thing you can do to logically order your data to improve query performance. The Lakehouse and the Delta Lake table format are central to Microsoft Fabric, assuring that tables are optimized for analytics is a key requirement. The data that gets cached might not be updated if the table is accessed using a different identifier. Dec 8, 2022 · Delta Lake change data feed - delete, vacuum, read - java. 0 to 3. Jan 30, 2025 · Delta Lake is a powerful storage layer built on top of Apache Spark, designed for reliability, performance, and scalability. Dec 7, 2022 · Conclusion Delta Lake makes it easy for you to remove rows of data from your Delta table. For performance improvements, I'm compacting and Apr 17, 2024 · I think the history can still include references to some parquet files which are now deleted, because the history log is not deleted by the vacuum operation (see next comments). This guide delves into key optimization techniques—Z-Ordering, Optimize Command, Optimize Write, Change Data Feed, Vacuum, Partitioning, and MERGE Performance Improvements Feb 1, 2025 · Introduction The VACUUM command in Delta Lake is used to delete old files no longer referenced by the transaction log, helping to optimize storage and maintain performance. Jun 4, 2021 · I'm trying to vacuum my Delta tables in Databricks. I have set the following table Feb 24, 2025 · Vacuum VACUUM command triggers Spark jobs to delete and remove excess stale data files in the root Delta Lake table directory that are no longer needed for queries. 1 or later. enabled to true so that the VACUUM operation will perform deletes in parallel. It reduces the number of write transactions as compared to the OPTIMIZE command. Here are the key reasons: Audit and History Tracking Apr 15, 2025 · Work with Delta Lake tables in Microsoft Fabric Working with Delta Tables in Microsoft Fabric opens up powerful capabilities for data management and analytics at scale. Azure Databricks Learning: Delta Lake - Vacuum Command========================================================What is Vacuum Command in delta table and how t Nov 8, 2024 · Learn to analyze Delta tables in Microsoft Fabric, improve performance, and understand key metrics and best practices in this comprehensive guide Nov 8, 2024 · Learn to analyze Delta tables in Microsoft Fabric, improve performance, and understand key metrics and best practices in this comprehensive guide Vibrant connector ecosystem: Delta Lake has connectors read and write Delta tables from various data processing engines like Apache Spark, Apache Flink, Apache Hive, Apache Trino, AWS Athena, and more. 4. spark. Please Feb 10, 2023 · Authors: KranthiMedam, InnovatorsClub, dipakshaw In every data engineering program, there is a need for upkeep on a Delta Lake. You can use Delta Lake with S3 using many different query engines. This configuration balances scalability and performance, ensuring optimal use of resources during both listing and deletion phases. Removing these files can Jul 14, 2025 · Solution Databricks recommends that you set a VACUUM retention interval to at least 7 days because old snapshots and uncommitted files can still be in use by concurrent readers or writers to the table. 8. Consider a base Delta Lake table, daily_user_actions, which represents the possible actions our users can take every day. 000001 hours so we can run this vacuum command right away. Apr 17, 2024 · That's true. 5. By using the enhanced capabilities of delta tables, you can create advanced analytics solutions. Let’s dive into the highlights: Identity columns assign Dec 21, 2021 · The linked article references the feature of the Delta on Databricks where it will try to produce bigger files when writing data - this is different from the automatic execution of OPTIMIZE/VACUUM. Delta Vacuum Purpose: Delta Lake maintains transaction logs, and older files may not be deleted immediately to support time … Jul 5, 2025 · A thought-provoking exploration of Delta Lake’s VACUUM command. enabled", false) orders. This connector is available as an inline dataset in mapping data flows as both a source and a sink. See the Delta Lake API documentation for Scala/Java/Python syntax details. Delta Lake is fully compatible with Apache Spark APIs, and was developed for tight integration Delta Lake — The Lakehouse Format Delta Lake is an open format storage layer that delivers reliability, security and performance on your data lake. Lower the checkpoint interval (delta. Jul 15, 2021 · Delta Lake has a safety check to prevent you from running a dangerous VACUUM command. May 21, 2022 · Delta lake is an open-source storage layer with support of ACID transactions to Apache Spark and big data workloads. Optimizing your Delta Lake table to avoid the Small File Problem is a great way to improve your out-of-the-box performance. Delta Lake optimizations may not make sense for you if you need the lowest write latency possible. enabled to false in your Spark config. load("Sample_Data") df. The Change Data Feed is useful for auditing, quality control, debugging, and intelligent downstream updates. Nov 5, 2025 · Delta Lake is the optimized storage layer that provides the foundation for tables in a lakehouse on Databricks. This guide covers Delta Lake table optimization concepts, configurations and how to apply it to most common Big Data usage patterns. enabled configuration property Feb 21, 2025 · Pyspark Optimization Technique — Vacuum, Time Travel and Z-OrderBy 1. vacuum(0) Note: setting the retention period to zero will prevent you from being able to rollback and time travel to previous versions. 0 is supported with the Data Flow Spark 3. Mar 12, 2025 · Learn how the VACUUM operation in Microsoft Fabric enables you to manage storage and preserve integrity of partitioned Delta tables. Oct 8, 2025 · Delta table streaming reads and writes This page describes how to stream changes from a Delta table. 3 how to use Python and the new Python APIs in Delta Lake 0. Data lakes do not support time travel. 0 processing engine, Delta Dec 9, 2022 · テーブルに対して vacuum コマンドを実行することで、保持期間よりも古くて、Deltaテーブルによって参照されていないファイルを削除することができます。 vacuum は自動では起動されません。 ファイルに対するデフォルトの保持期間は7日間です。 Oct 3, 2019 · In this blog, we will demonstrate on Apache Spark™ 2. 2. This process Apr 30, 2025 · In the cluster spark configuration, we will set spark. One of the newer features in Delta Lake is the concept of deletion vectors, which enhance its Delta Lake abstract the file metadata to a transaction log and support Z Ordering, so you can run queries faster. Does it mean, it only touches the delta logs for deleted columns or data and not the actual data? Jul 5, 2023 · How Deletion Vectors in Delta Lake work Let’s explore how this table feature works with the Spark Delta Lake connector. By default, when a single row in a data file is deleted, the entire Parquet file containing the record must be rewritten. Manage Retention: Clean old versions with VACUUM: delta_table. . In some instances, Delta lake needs to store multiple versions of the data to enable the rollback feature. 3 (release notes) on Apache Spark 3. Jul 14, 2023 · The Delta Lake Change Data Feed (CDF) allows you to automatically track Delta table row-level changes. One essential maintenance task for Delta Lake is vacuuming. com You’ve learned about how the vacuum command works and the tradeoffs in this post so you can properly clean up old files in your Delta tables. 0 that adds a decoupled client-server infrastructure which allows remote connectivity from Spark from everywhere. data lake support Delta Lake makes it easy to time travel between different versions of a Delta table. The default retention Jul 8, 2024 · Delta Lake is a storage layer that brings ACID transactions to Apache Spark and big data workloads. This void led to the emergence of data lakes, offering a promising solution by accommodating diverse data Feb 8, 2024 · VACUUM will remove Delta table data files that are no longer in the latest state of the transaction log for the table and are older than a retention threshold. conf. enabled", "false") delta_table. Apr 30, 2025 · Data Flow supports Delta Lake by default when your Applications run Spark 3. "set spark. Oct 9, 2020 · Vacuum operation should be performed to delete older & not referenced (not active) file. Oct 12, 2024 · Conclusion To sum up, VACUUM in Delta Lake is like cleaning up after a party. Feb 1, 2023 · Delta Lake time travel vs. Delta Lake is fully compatible with Apache Spark APIs, and was developed for tight integration with Structured Streaming Nov 28, 2024 · Optimize Microsoft Fabric Lakehouse and delta lake performance delta lake tutorial 6 : What is Delta Lake Vacuum #deltalake #vacuum #databricks #delta #sqlintroduction To Delta Lake : What is Delta Lake, What is Azure D Nov 1, 2022 · This post explains the append and overwrite PySpark save mode write operations and how they’re physically implemented in Delta tables. The feature is enabled by a configuration setting or a table property. So for testing, I have set the delta. 🚨 Common issues with VACUUM in Delta tables: VACUUM takes too long or fails to complete. For example, any old data files from previous Delta Lake versions that remain after running OPTIMIZE command. There's no need to change the spark. Jul 12, 2024 · It's available on Delta Lake tables for both Batch and Streaming write patterns. Notice for the reiterator table, there are 10 distinct time-buckets, as we’re starting from a later transaction version of the table. sql("alter table delta. Along with migration, Delta Sharing has also added support for Delta Lake tables with advanced features like Deletion Vectors and Column Mapping. I was confused with the version timestamp, VACUUM keeps files for the active version at that time, I thought it kept files of versions with higher timestamp only. Nov 10, 2025 · What are deletion vectors? Deletion vectors are a storage optimization feature you can enable on Delta Lake tables. You can optimize your Delta Lake tables: Welcome to Delta Lake’s Python documentation page ¶ DeltaTable ¶ class delta. For Azure, ensure proper configuration of ADLS Gen2 storage. Jul 2, 2024 · Delta Lake with Apache Spark After years of data management, data warehouses reigned supreme with their structured storage and optimized querying. We will show how to upsert and delete data, query old versions of data with time travel and vacuum older versions for cleanup. Aug 2, 2019 · Delta Lake has a safety check to prevent you from running a dangerous VACUUM command. Learn how to keep your Delta Lake tables optimized across multiple scenarios, and how V-Order helps with optimization. `[delta_file_path]` set TBLPROPERTIES (’delta. Vacuum deletes all unreferenced files. I was reading this blog post for vacuuming delta tables and as far as I understand, running vacuum on AWS is a single threaded process May 18, 2025 · Learn how to optimize Delta tables in Apache Spark using techniques like OPTIMIZE, Z-ORDER, VACUUM, caching, and efficient partitioning. When you’re reading a data lake, you always have to read the latest version. Jun 20, 2025 · If you run VACUUM on a Delta table, you lose the ability to time travel back to a version older than the specified data retention period. Delta Lake is deeply integrated with Spark Structured Streaming through readStream and writeStream. Thank you 😀 Apr 26, 2021 · I can see an example on how to call the vacuum function for a Delta lake in python here. May 1, 2025 · spark. 0 within the context of an on-time flight performance scenario. However the actual data files (parquet files) in your lakehouse table's file directory should be deleted by vacuum operations (according to vacuum retention threshold). These settings help Apache Spark correctly handle Delta Lake tables. `{delta_table_path}` RETAIN 7 DAYS") Theory Note: Never set VACUUM retention below 7 days if you have streaming jobs, as they might need to read older files. Feb 19, 2025 · Delta Lake retains table versions based on the retention threshold for transaction log files and the frequency and specified retention for VACUUM operations. apache. The VACUUM command deletes old versions of the data files permanently based on the Audit Regularly: Use history () to track changes Spark Delta Lake versioning. data bricks. After every run, where new data is merged, we call vacuum with 0 hour retention to remove old files and run optimize comm Feb 19, 2025 · spark. Sep 28, 2023 · Find out how to use the optimizations of your Delta Lake to increase the performance of the operations and save costs. In Databricks Runtime, you are certain that there are no operations being performed on this table that take longer than the retention interval you plan to specify, you can turn off this safety check by setting the Spark configuration property spark. Jan 12, 2021 · The Vacuum command can be used to clean the unused files. Delta Lake Optimization Project: Hands‑on lab to explore partitioning, Z‑Ordering, compaction (manual &amp; auto), Liquid Clustering, and VACUUM using a synthetic sales dataset in Databricks. Feb 3, 2023 · Why use VACUUM on Delta Lake? VACUUM is used to clean up unused and stale data files that are taking up unnecessary storage space. Reading documentation, I see that this command removes parquet files that are not being used for versions above the retention period, but I'm testing and it's no working. df = spark. This blog post shows you how to enable the Change Data Feed and demonstrates common workflows in Oct 8, 2023 · If you are using Spark w/ Delta Lake 2. FileNotFoundException Asked 2 years, 11 months ago Modified 2 years, 11 months ago Viewed 1k times Jun 24, 2025 · Run Delta Lake OPTIMIZE and VACUUM periodically to compact files (though note that vacuum only cleans obsolete data files—not delta logs themselves). In the realm of big data, efficiency is paramount. If you run VACUUM with the default settings, you will only be able to time travel up to the last 7 days. delta The standard Delta vacuum operates in three stages. Delta Lake overcomes many of the limitations typically associated with streaming systems and files, including: Coalescing small files produced by low latency ingest. Apr 16, 2024 · I don't have very clear how VACUUM command works. Legacy configurations can prevent new optimizations and default values introduced by Databricks from being applied to migrated workloads. Wanted to explore new VACUUM xxx LITE mode but whenever I run it, I get org. Do not set spark. Jun 3, 2024 · Hi, Is delta table maintenance managed by Fabric? Does Fabric do managed vacuuming of my Lakehouse tables (behind the scenes)? Or will my Lakehouse delta tables be accumulating all table historical data (version history), until I decide to do a vacuum myself. You can use history information to audit operations, rollback a table, or query a table at a specific point in time using time travel. enabled = false; VACUUM your_table_name RETAIN 0 HOURS; Alternative: If you must permanently remove data for compliance or privacy reasons, consider using the DELETE command or DROP TABLE instead of VACUUM. Improve query performance and reduce latency with these Delta Lake best practices. spark. Alternatively, you can set the following configuration using SparkConf in your script. Upsert to a table. It’s a straightforward operation that’s a natural extension of the Delta Lake transaction log. io. This blog presents a way to automate such a maintenance process in Synapse Analytics. Apr 28, 2025 · Optimizing Spark + Delta Lake with Partitioning, ZORDER, and VACUUM As modern data systems grow in scale, the need for optimized data storage and fast query performance becomes critical. Some of these engines require some additional configuration to get up and running. It enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive, and APIs for Python, SQL, Scala, Java, Rust, and Ruby. sql("VACUUM delta. parallelDelete. The first stage involves performing a recursive listing of all the files under the Delta Lake table while eliminating certain hidden files and folders. To get started follow the quickstart guide to learn how to use Delta Lake with Apache Spark. Microsoft Fabric's Delta Lake tables offer a robust solution for managing large datasets, but to harness their full potential, proper optimization is essential. 0 Try out Delta Lake with the preceding code snippets on your Apache Spark 3. Jan 9, 2024 · Delta Lake is built on top of Apache Spark and provides a reliable and scalable data lake solution. If predictive optimization is enabled, Databricks automatically triggers the VACUUM operation as part of its optimization process. Jan 15, 2025 · This issue occurred after running a **Vacuum** operation. enabled to false. On other hand, if you perform 'vacuum' with 30 days retention, you can access last 30 days data. Get Started with Delta Lake 0. Running vacuum doesn’t make your Delta Lake operations any faster, but it removes files on disk, which reduces storage costs. vacuum(168) # Retain 7 days Use Streaming Wisely: Combine with checkpointing PySpark streaming checkpointing. Inclu Oct 15, 2024 · Delta Lake is an open-source data lake storage layer that provides ACID (Atomicity, Consistency, Integrity, and Durability) transactions, versioning, schema enforcement, and other advanced Aug 7, 2023 · Delta Lake runs on top of your existing data lake and is fully compatible with Apache Spark APIs. microsoft. You may need to convert a Delta Lake to a Parquet lake if a downstream system is unable to read the Delta Lake format. Feb 11, 2025 · Learn the fundamentals of Delta Lake, from setup to advanced features like time travel and schema evolution—a must-read for data engineers and analysts. DeltaTable(spark: pyspark. Aug 21, 2023 · Unlocking Performance: Optimize, Vacuum, and Z-Ordering in Databricks’ Delta Tables Delta Lake is a powerful storage layer that brings ACID transactions to Apache Spark and big data workloads … Attempting to vacuum the delta table (even with DRY RUN) gives an IllegalArgumentException because of the default values of the following: spark. Files are not deleted as Oct 3, 2022 · We’ll look at that command and its effects next. Mar 13, 2025 · Learn how to optimize and vacuum your Microsoft Fabric lakehouse tables for better performance and efficiency. checkpointInterval) so checkpoints are created more frequently, allowing Spark to skip many JSON logs and list/parse fewer files during state reconstruction. Yes, it solves querying across dataset versions. Delta tables are a core abstraction in Delta Lake, which are … Spark Delta Lake | Vacuum or Retention in Spark Delta Table with Demo | Session 5 | LearntoSpark Azarudeen Shahul 14. Catalog Explorer provides a visual view of this detailed table information and history for Delta tables. : Feb 21, 2025 · Tables in a Microsoft Fabric lakehouse are based on the Delta Lake technology commonly used in Apache Spark. 3, with features that improve the performance and interoperability of Delta Lake. You can run the example Python, Scala, and SQL code in this article from within a notebook attached Jul 3, 2023 · Optimizing Delta Tables using Vacuum and Optimize Delta Lake is an open-source storage layer that brings reliability to data lakes. logRetentionDuration'='interval 2 da Feb 13, 2025 · This article highlights how to copy data to and from a delta lake stored in Azure Data Lake Store Gen2 or Azure Blob Storage using the delta format. Parquet lakes are still useful when you’re interfacing with systems that don’t support Delta Lake. Delta Lake restore after vacuum vacuum is a widely used command that removes files that are not needed by the latest version of the table. The process I have impalement as POC and It has been tested … Nov 3, 2021 · Reorganize a Delta Lake table by rewriting files to purge soft-deleted data, such as the column data dropped by ALTER TABLE DROP COLUMN. parquet("Sample_Data") df Example (For Demonstration Only – Do Not Use in Production) SQL SET spark. After the option "enabled = False" was given, the command "VACUUM del_park retain 0 hours;" was used, but the history remained unchanged I want to erase history based on 0 hours, what should I do? Existing users of delta-sharing-spark Maven artifact have to upgrade their version from <= 1. A Deep Dive into Tracking Data Changes Efficiently 🚀 Introduction Imagine you have Oct 9, 2023 · Vacuum No, this isn’t a blog post about the best vacuum brands, however I do want to share how you can keep your Delta Table clean and tidy via performing the vacuum operation. I'm using EMRFS. Test Rollbacks: Practice in a staging environment Spark Delta Lake rollback using time travel. Delta Lake Clone Delta Lake clone gives you data copying functionality with varying degrees of control and flexibility. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing on top of existing data lakes. enabled configuration property). You’ll see how these operations are implemented differently for Parquet tables and learn why the Delta Lake implementation is superior. The Delta Lake delete operation is executed efficiently because it only rewrites the minimal subset of files. 0 job) to write data to a Delta ta Jan 13, 2024 · I am trying to optimize my vacuum/optimize jobs on databricks. Jan 18, 2023 · Delta Lakes can be converted to “regular Parquet data lakes” by setting the retention period to zero, running the vacuum command, and deleting the _delta_log directory. But how do I call it for only a dry run? In other words, what is the equivalent Python code for the followin Delta Lake supports most of the options provided by Apache Spark DataFrame read and write APIs for performing batch reads and writes on tables. enabled", "false") For S3, use S3-specific consistency checks: Enable S3 Guard or AWS Glue Data Catalog for consistency management. Even on Databricks, you need to run VACUUM explicitly - just create a small Spark job that will execute VACUUM on selected table (s) - just follow documentation for correct syntax & settings. For Spark SQL syntax details, see DESCRIBE HISTORY. databricks. Jul 17, 2024 · In the final installment of our blog series on optimizing data ingestion with Spark in Microsoft Fabric, we delve into advanced optimization techniques and essential maintenance strategies for Delta tables. logRetentionDuration = 2 days using the below command spark. In the second stage, the set of actively referenced files from the Delta log is joined with the file list collected from the first stage. See Configure SparkSession. Spark Connect is a new project released in Apache Spark 4. Storing multiple versions of the same data can get expensive, so Delta lake includes a vacuum command that deletes old versions of the data. 5K subscribers Subscribed Jul 15, 2022 · Vacuum and Compaction go through the _delta_log/ folder in your Delta Lake Table and identify the files that are still being referenced. With Delta Lake providing atomic transac‐ tionalityfor your data, this allows you - the data practitioner - to need to only focus on building your data processing pipelines by expressing the processing. Delta Lake’s implementation of the Change Data Feed is fast, scalable, and reliable. Maintaining “exactly-once Feb 8, 2024 · Delta Lake brings ACID transactions to Apache Spark, offering data versioning, schema enforcement, lineage, and more commands for efficient data management. Feb 28, 2022 · The below example will show you how the data get maitained in the Delta lake. Nov 4, 2025 · Work with Delta Lake table history Each operation that modifies a Delta Lake table creates a new table version. By utilizing an inventory table, the VACUUM operation selectively processes only the files listed, bypassing the labor-intensive task of scanning the entire directory of a table. Let's run the vacuum command and verify the file is deleted in the filesystem. retentionDurationCheck. sczupo cqociux ctqkf ocugzq gbjumq lkpu gpjn vrvdx dcvi umy eoteiy ply fghli zorrmsk cbf