Spark optimal file size. AWS recommends avoiding having files less than 128MB.

Spark optimal file size maxPartitionBytes : 1024mb : I know from the Delta Lake documentation that the "optimal" (Parquet) file size is 1gb, but I don't really know why. When you load a 10GB file, Spark does not load it Jan 9, 2025 · Writing to Parquet files in Apache Spark can often become a bottleneck, especially when dealing with large, monolithic files. 7. Enable file-level compaction targets to prevent write amplification as tables grow in size and use larger target file sizes. Too small, and query performance suffers from excessive metadata Large number of small files is not a Spark problem. 0. optimize. Monitor and Optimize Data Layout Dec 27, 2019 · Spark. s3a. Auto compaction is only triggered for partitions or tables that have at least a certain number of small files. toString) You need to make sure that each partition is big Aug 28, 2016 · In spark, what is the best way to control file size of the output file. For example, in log4j, we can specify max file size, after which the file rotates. Too small, and query performance suffers from excessive metadata Nov 28, 2024 · Optimizing Small File Management in Apache Spark Handling a large number of small files is a common challenge in Big Data environments, especially when working with CDC data in a data lake. Monitor and Optimize Data Layout Learn how to set the spark. Nov 9, 2020 · However, in this blog using the native Scala API I will walk you through two Spark problem solving techniques of 1. A previous 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. Those techniques, broadly speaking, include caching data, altering how datasets are partitioned, selecting the optimal join strategy, and providing the optimizer with additional information it can use to build more efficient execution plans. Too small, and query performance suffers from excessive metadata Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. Are there any best practices around: Preferred File Formats for how I store my data in S3? (does the format even matter?) Optimal file size? Aug 16, 2023 · This blog covers performance metrics, optimizations, and configuration tuning specific to OSS Spark running on Amazon EKS. Discover key Apache Spark optimization techniques to enhance job performance. Is there a guideline on how to select the most optimal number of partitions and buckets for my dataframe? My initial dataset is about 200GB (billions of rows, more than 30 billion rows), the “id” field in my data repeats and represents a set of events, each grouping of id’s has varying frequencies resulting in data skew. parquet("file-path") My question, though, is whether there's an option to specify the size of the resultant parquet files, namely close to 128mb, which according to Spark's documetnation is the most performant size. The relation between the file size, the number of files, the number of Spark workers and its configurations, play a critical role on performance. files. Learn to debunk misconceptions, optimize code with DataFrames and caching, and improve efficiency through configuration and storage-level tweaks. In this guide, we’ll explore best practices, optimization techniques, and step-by-step implementations to maximize PySpark’s performance when working with large-scale data. Sep 8, 2016 · Actually there exists some sort of heuristic computation to help you to determine the number of cores you need in relation to the dataset size. So create 1000 single line files, the system need to allocate 128000 M of memory. Jul 10, 2019 · I need to read data (originating from a RedShift table with 5 columns, total size of the table is on the order of 500gb - 1tb) from S3 into Spark via PySpark for a daily batch job. Caching Data Tuning Partitions Coalesce Hints Does anyone here have experience with trying to optimize the batchsize for spark. Apr 10, 2025 · Reading large files in PySpark is a common challenge in data engineering. min. You can optionally change the minimum number of files required to trigger auto compaction by setting spark. (but this has a cost of course, an extra shuffle) But be aware that there is no single optimal file size. Speedup if you have idle workers. When reading a table, Spark defaults to read blocks with a maximum size of 128Mb (though you’ll be able to change this with sql. This blog post provides a comprehensive guide to spark. size (by default 128 MB) Optimized files are written in a directory called as file name with an _optimized append to its name. Apr 25, 2023 · First of all, the size of Parquet file does not matter itself. If this property is set, all data layout optimization operations will make a best-effort attempt to generate files of the specified size. To address the issue of data skew which I’m assuming is making my Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. Nov 9, 2022 · Explore compaction in Apache Iceberg for optimizing data files in your tables. Too small, and query performance suffers from excessive metadata Sep 15, 2025 · Optimize write reduces small-file overhead by performing pre-write compaction (bin packing), which generates fewer, larger files. Aug 11, 2023 · Unlock optimal I/O performance in Apache Spark. Tasks: One task per partition reads a block, executed by executors Spark Tasks. Too small, and query performance suffers from excessive metadata Oct 21, 2024 · Best Practice: Consolidate small files into larger Parquet files whenever possible. The 200 partitions might be too large if a user is working with small data, hence it can slow down the query. One key factor in achieving optimal performance is the choice of file format for storing data. set (“spark. size (by default 100 MB ), all files with same extension in the same directory will be merged to reach an optimal size defined by spark. Apr 2, 2025 · 📊 Optimal File Formats for Big Data 📝 CSV vs. targetFileSize setting doesn't guarantee that the file size will be exactly as configured. Ingestion workloads into data lake tables could have the inherited characteristic of constantly writing lots of small files; this scenario is commonly known as the "small file problem". toString) You need to make sure that each partition is big First of all, the size of Parquet file does not matter itself. I don't know what it is for s3/dbfs/ but it isn't zero. Learn how to fine-tune and boost data performance. Performance is top of mind for customers running streaming, extract transform load […] Mar 9, 2025 · Apache Spark is designed for distributed computing, meaning it breaks large files into smaller chunks (partitions) and processes them in parallel. Jan 22, 2019 · You can control the split size of parquet files, provided you save them with a splittable compression like snappy. Jun 13, 2023 · With coalesce and repartition you can define the number of partitions (files) that will be written. When writing Parquet files to S3, EMR Spark will use EMRFSOutputCommitter which is an optimized file committer that is more performant and resilient than FileOutputCommitter. ORC vs. maxFileSize The default setting of 1GB files works best in most scenarios. The code is separated into 2 parts, one calculates the Optimal Number of Partitions for the defined sizer per file, and the other writes the data with the specified size. What Are Spark Partitions? Mar 27, 2024 · How to tune Spark’s number of executors, executor core, and executor memory to improve the performance of the job? In Apache Spark, the number of cores and the number of executors are two important configuration parameters that can significantly impact the resource utilization and performance of your Spark application. For the s3a connector, just set fs. For Spark, Parquet file format would be the best choice considering performance benefits and wider community support. One often-mentioned rule of thumb in Spark optimisation discourse is that for the best I/O performance and enhanced parallelism, each data file should hover around the size of 128Mb, which is the default partition size when reading a file [1]. As the number of files in a table increases, so does the size of the metadata files. optimal. Usually if you like to read the entire Jun 28, 2017 · Spark 2. targetFileSize or preferably adaptive target file size to keep target file size values consistent across data layout features and Spark sessions. Parquet vs. More startup overhead scheduling work, starting processing, committing tasks Creates more files Jun 17, 2019 · It's not duplicate. Apr 14, 2018 · I have 160GB of data,partition on DATE Column and storing in parquet file format running on spark 1. Read properties Write properties Table behavior properties Reserved table properties Reserved table properties are only used to control behaviors when creating or updating a table. Optimizing query performance involves minimizing the number of small files in your tables. Discover best practices and strategies to optimize your data workloads with Databricks, enhancing performance and efficiency. So how do I figure out what the ideal partition size sh This pattern shows you how to optimize the ingestion step of the extract, transform, and load (ETL) process for big data and Apache Spark workloads on AWS Glue by optimizing file size before processing your data. Feel free to clarify that last point as well if you know! Mar 27, 2025 · PySpark, the Python API for Apache Spark, provides a scalable, distributed framework capable of handling datasets ranging from 100GB to 1TB (and beyond) with ease. coalesce( numberOfElements / magicNumber) Is there any rule of thumb about the optimal number of partition of a RDD and its number of elements ? Thanks. Partitioning: Spark creates partitions based on HDFS block size (e. File size also impacts query planning for Iceberg tables. Too small, and query performance suffers from excessive metadata Aug 11, 2023 · The variety of output files saved to the disk is the same as the variety of partitions within the Spark executors when the write operation is performed. Delta Lake is an option, which has some automated file optimizations. maxPartitionBytes), it is usually 128M and it represents the number of bytes form a dataset that's been to be read by each processor. size to a different number of bytes. Basic solution is to merge your The Small File Problem gets referenced a lot when discussing performance issues with Delta Lake queries. Avro 🗜️ Compression Techniques ️ Splittable vs. Feb 18, 2015 · This all depends on the dataset size and specific use cases, but, in general, we've seen that Parquet partitions of about 1GB are optimal. Optimize write should be cautiously Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. Use repartition(8) if Spark's default partitioning isn't efficient. Big fs block size is feature, not a bug. For Mar 27, 2024 · In this article, we shall discuss Apache Spark partition, the role of partition in data processing, calculating the Spark partition size, and how to modify partition size. It parts form a spark configuration, the partition size (spark. We’re introducing two powerful file size management features in Microsoft Fabric Spark: use defined Target File Size and Adaptive Target File Size. Feb 3, 2025 · The OPTIMIZE command in Databricks consolidates multiple small files into larger files, aiming for an optimal size (typically up to 1GB for Parquet files). 6. Use coalesce Mar 23, 2025 · Picture yourself at the helm of a large Spark data processing operation. . Feb 14, 2024 · Take advantage of the filter option in the rewrite data files spark action to best select the files to be rewritten based on your use case so that no delete conflicts occur. Performance Tuning Spark offers many techniques for tuning the performance of DataFrame or SQL workloads. Use this pattern to prevent or resolve the small files problem. 2+ From Spark 2. sql. For good query performance, we generally recommend keeping Parquet and ORC files larger than 100 MB. Non-Splittable Files 📖 Reading Large Files Efficiently 🧩 Partitioned Reads 🔍 Predicate Pushdown & Column Pruning 🧮 Chunked Processing 🧠 Memory Management & Optimization 💾 Spill-to-Disk Strategies Feb 11, 2025 · I have personally been able to speed up workloads by 15x by using this parameter. databricks. You will still get at least N files if you have N partitions, but you can split the file written by 1 partition (task) into smaller chunks: df. In this blog, we’ll look at how different file formats can improve Spark’s efficiency and help you get the most out of your data processing. Dive deep into partition management, repartition, coalesce operations, and streamline your ETL processes Mar 2, 2025 · Best Approach for a 2GB CSV File on Local Spark Read with at least 8 partitions (4 cores × 2 partitions per core). Includes references for deeper insights. Currently doing data. size", desiredBlockSize. toInt. This approach shuffles in-memory data into optimally sized bins before Spark writes the Parquet files, maximizing the potential for generating appropriately sized files without requiring immediate post-write cleanup operations. Caching Data Tuning Partitions Coalesce Hints Sep 11, 2024 · Overview Apache Spark is a powerful big data analytics tool known for its speed and scalability. maxPartitionBytes”, 1024 * 1024 * 128) — setting partition size as 128 MB Apply this configuration and then read the source file. Aim for file sizes in the range of 128 MB to 1 GB, depending on your system’s memory and processing capacity. Jun 9, 2021 · Spark by default uses 200 partitions when doing transformations. maxPartitionBytes governs their size, and best practices for optimizing it. I know Snowflake is Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. You don’t usually need to play with this. set("parquet. For customers using or considering Amazon EMR on EKS, refer to the service documentation to get started and this blog post for the latest performance benchmark. option("maxRecordsPerFile", 10000) Jul 4, 2021 · data. Is your data properly partitioned? Having too many partitions can lead to smaller files being created. Jan 27, 2021 · Im using pyspark and I have a large data source that I want to repartition specifying the files size per partition explicitly. Discover how data compaction, Z-ordering, file size optimization, and more can significantly enhance the performance and efficiency of your data operations. Too small, and query performance suffers from excessive metadata I'm researching best practices for partitioning dataframes and from my initial impressions via google search it seems like there's two conflicting… Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. write. write . Caching Data Tuning Partitions Coalesce Hints Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. That is, when a large number of small files slows down data processing due to the aggregate size of the files. Imagine your files as vessels navigating the sea Jun 13, 2023 · But on the other hand, I don't know it can decrease the performance when telling Spark to use spark. Mar 15, 2016 · val numberOfElements = rdd. Too small, and query performance suffers from excessive metadata Oct 14, 2025 · Worse yet, the optimal file size for a 10GB table is completely different from the optimal size for a 10TB table—and most tables don’t stay the same size forever. Too small, and query performance suffers from excessive metadata Sep 3, 2024 · spark. minNumFiles. Configuration Table properties Iceberg tables support table properties to configure table behavior, like the default split size for readers. autoCompact. Mar 7, 2019 · I'm trying to work out what the optimal file size when partitioning Parquet data on S3. That question maybe answer first part of my question although that's not the same (why is this happend?) but my main question is: what is the optimum number of partition when writing to a parquet file? Feb 4, 2025 · Set a target file size If you want to tune the size of files in your Delta table, set the table property delta. Mar 18, 2023 · PySpark — Optimize Huge File Read How to read huge/big files effectively in Spark We all have been in scenario, where we have to deal with huge file sizes with limited compute or resources. Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. Aug 11, 2023 · Photo by zhao chen on Unsplash Picture yourself at the helm of a large Spark data processing operation. There's is a minimal file system block size on PC it is 4-8 K, Hadoop default 64-128 M. Definitely worth trying out. 2 on, you can also play with the new option maxRecordsPerFile to limit the number of records per file if you have too large files. This article explores how to optimize Parquet file writes by splitting Sep 16, 2025 · Use delta. I need to store the output parquet files with equal sized files in each partition with fixed Oct 14, 2025 · Worse yet, the optimal file size for a 10GB table is completely different from the optimal size for a 10TB table—and most tables don’t stay the same size forever. Too small, and query performance suffers from excessive metadata Jun 28, 2017 · Spark 2. However, choosing the right file format for your data is crucial to get the best performance from Spark. maxPartitionBytes property to optimize your Spark SQL jobs for large datasets. But is there also a recommended maximum file size? Nov 5, 2024 · Best Practice: Consolidate small files into larger Parquet files whenever possible. Thanks in advance! Archived post. Too small, and query performance suffers from excessive metadata Feb 27, 2024 · However, optimizing Spark jobs for performance remains a significant challenge. parquet results in files between 10-20mb, which I suspect is affecting the performance of my If files are smaller than spark. When you’re working with a 100 GB file, default configurations… Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. , 128MB blocks for a 1GB file ≈ 8 partitions). delta. Oct 3, 2024 · The aim of this article is to provide a practical guide on how to tune Spark for optimal performance, focusing on partitioning strategy, shuffle optimization, and leveraging Adaptive Query Execution… Learn some performance optimization tips to keep in mind when developing your Spark applications. Oct 21, 2024 · Best Practice: Consolidate small files into larger Parquet files whenever possible. g. block. They will use byte-range fetches to get different parts of the same S3 object in parallel. It kills any big data tool performance. Reading happens by row groups, so it is the row group size you must optimize, if you care about query performance. You may need to adjust the number of partitions using repartition() or coalesce() before writing. I know using the repartition(500) function will split my parquet into Oct 14, 2025 · Set It and Forget It Target File Size Optimization What if you could enable a single setting and never worry about file size tuning again? Or if your tables automatically adjusted their optimal file sizes as they grew from megabytes to terabytes, without any manual intervention? Today’s data teams face a familiar challenge. files Jan 2, 2025 · This article delves into the importance of partitions, how spark. This setting controls the maximum size of each Spark SQL partition, which can help to improve performance by reducing the amount of data that needs to be processed by each Spark executor. count() val magicNumber = 100000 rdd. Smaller split size More workers can work on a file simultaneously. jdbc () and if so, did it make a big difference? My goal here is to write some sort of function that returns optimal batchsize given the specific dataframe, cluster, partitions and so on. For smaller datasets, however, this large partition size may limit parallelism as tasks operate on individual partitions in parallel, so please keep that in mind. Too small, and query performance suffers from excessive metadata Delta Lake Optimize maxFileSize You can set the maximum file size of your files with the maxFileSize config option: spark. Oct 14, 2025 · Worse yet, the optimal file size for a 10GB table is completely different from the optimal size for a 10TB table—and most tables don’t stay the same size forever. Too small, and query performance suffers from excessive metadata Jan 12, 2020 · Optimising size of parquet files for processing by Hadoop or Spark The small file problem One of the challenges in maintaining a performant data lake is to ensure that files are optimally sized Feb 4, 2025 · See Autotune file size based on workload and Autotune file size based on table size. Examples here include optimize or Z-order, auto compaction, and optimized writes. Many sources recommend file sizes of 1GB for optimal query performance. Nevertheless, gauging the variety of partitions before performing the write operation might be tricky. ) how to include a transient timer in your Spark Structured Streaming job for gracefully auto-terminating periodic data processing appends of new source data, and 2. targetFileSize to the desired size. In Spark, the row group size can be controlled like this val desiredBlockSize = 512L * 1024 * 1024L spark. Tools like Apache Spark or Apache Hudi offer mechanisms for compaction to combine small files into larger ones. Learn the practical steps to Performance Tuning Spark offers many techniques for tuning the performance of DataFrame or SQL workloads. conf. maxPartitionBytes, exploring its impact on Spark performance across different file size scenarios and offering practical recommendations for tuning it to achieve optimal efficiency. I am looking for similar solution for p May 23, 2019 · the optimal file size depends on your setup if you store 30GB with 512MB parquet block size, since Parquet is a splittable file system and spark relies on HDFS getSplits() the first step in your spark job will have 60 tasks. AWS recommends avoiding having files less than 128MB. It serves more as a hint to the optimizer. Conversely, the 200 partitions might be too small if the data is big. Let's take a deep dive into how you can optimize your Apache Spark application with partitions. Aug 29, 2023 · Solving the Small File Problem in Iceberg Tables The Data Platform team at Ancestry has been maintaining a fully-refreshed 100-billion-row Apache Iceberg table for several months. ) how to control the number of output files and the size of the May 5, 2022 · When you're processing terabytes of data, you need to perform some computations in parallel. toaon muley tpyh fium swvhn jrj eyzfd pnd tbnqdb zrhv npswd ygapkx fzd mkm vgbxb