Скачать с ютуб File Formats [Row based vs Columnar Format] в хорошем качестве

File Formats [Row based vs Columnar Format]

If you need any guidance you can book time here, https://topmate.io/bhawna_bedi56743 Follow me on Linkedin   / bhawna-bedi-540398102   Instagram https://www.instagram.com/bedi_foreve... You can support my channel at: bhawnabedi15@okicici Row Based Format The Data is stored in rows such as: SequenceFile, MapFile, Avro Datafile. In this way, if only a small amount of data of the row needs to be accessed, the entire row needs to be read into the memory. Delaying the serialization can lighten the problem to a certain amount, but the overhead of reading the whole row of data from the disk cannot be withdrawn. Row-oriented storage is suitable for situations where the entire row of data needs to be processed simultaneously. Column Based Format The entire file cut into several columns of data, and each column of data stored together: Parquet, ORCFile. The column-oriented format makes it possible to skip unneeded columns when reading data, suitable for situations where only a small portion of the rows are in the field. But this format of reading and write requires more memory space because the cache line needs to be in memory (to get a column in multiple rows). At the same time, it is not suitable for streaming to write, because once the write fails, the current file cannot be recovered, and the line-oriented data can be resynchronized to the last synchronization point when the write fails, so Flume uses the line-oriented storage format. Data-bricks hands on tutorials    • Databricks hands on tutorial(Pyspark/...   Azure Event Hubs    • Azure Event Hubs   Azure Data Factory Interview Question    • Azure Data Factory Interview Questions   SQL leet code Questions    • SQL Interview Questions(LeetCode/Hack...   Azure Synapse tutorials    • Azure Synapse Analytics Hands-on Tuto...   Azure Event Grid    • Event Grid   Azure Data factory CI-CD    • CI-CD in Azure Data Factory   Azure Basics    • Azure Basics   Data Bricks interview questions    • DataBricks Interview Questions