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    8 Aug, 2024
    Optimize Pipelines for Analytical or Transactional Purposes – Troubleshoot Data Storage Processing-5
    Azure Monitoring Overview, Develop a Batch Processing Solution, Exams of Microsoft, Handle Skew in Data, Microsoft DP-203, Tune Queries by Using Cache

    The other option in the Compute Size drop‐down is Custom, which enables the Compute Type and Core Count boxes, allowing you to select up to 256 (+ 256 driver cores) for either Basic or Standard type. In addition to allowing

    Continue ReadingOptimize Pipelines for Analytical or Transactional Purposes – Troubleshoot Data Storage Processing-5

    25 May, 2024
    Optimize Pipelines for Analytical or Transactional Purposes – Troubleshoot Data Storage Processing-2
    Exams of Microsoft, Microsoft DP-203

    This code results in the creation of an updatable columnstore index on which OLAP operations can operate. Additionally, memory will be allocated to handle OLTP transactions that get regularly ingested into the columnstore index. This has effectively separated the OLTP

    Continue ReadingOptimize Pipelines for Analytical or Transactional Purposes – Troubleshoot Data Storage Processing-2

    30 Oct, 2023
    Tune Shuffle Partitions – Troubleshoot Data Storage Processing-3
    Azure Monitoring Overview, Develop a Batch Processing Solution, Exams of Microsoft, Microsoft DP-203

    For the Apache Spark pool perspective, refer to the “Design a Partition Strategy” section in Chapter 3. Methods like spark.conf.set(“spark.sql.shuffle.partitions”, 200) and df.rdd.getNumPartitions() provide insights and features for managing data partitions and shuffling. One final note concerning the number of

    Continue ReadingTune Shuffle Partitions – Troubleshoot Data Storage Processing-3

    8 Jul, 2023
    Handle Data Spill – Troubleshoot Data Storage Processing
    Azure Monitoring Overview, Develop a Batch Processing Solution, Exams of Microsoft, Microsoft DP-203, Tune Queries by Using Cache

    A data spill is the same as a data leak, which happens when protected data is transferred to an unauthorized person or stored in an unauthorized location. Data can be spilled by copying a protected file to a publicly accessible

    Continue ReadingHandle Data Spill – Troubleshoot Data Storage Processing

    22 Jan, 2023
    Find Shuffling in a Pipeline – Troubleshoot Data Storage Processing
    Azure Monitoring Overview, Develop a Batch Processing Solution, Exams of Microsoft, Handle Skew in Data, Microsoft DP-203

    Data shuffling was introduced in Chapter 2, where it was described as the movement of data from one node to another. When using the hash distribution model, remember that the distribution key provided to the HASH function determines how the

    Continue ReadingFind Shuffling in a Pipeline – Troubleshoot Data Storage Processing

    30 Dec, 2022
    Optimize and Troubleshoot Data Storage and Data Processing – Troubleshoot Data Storage Processing-2
    Exams of Microsoft, Handle Skew in Data, Microsoft DP-203, Tune Queries by Using Cache

    Performing I/O is inherently latent, so when you do it, it needs to be worth the effort. If your application code is frequently writing very small bits of data to disk, retrieving a single row from a database, or sending

    Continue ReadingOptimize and Troubleshoot Data Storage and Data Processing – Troubleshoot Data Storage Processing-2

    19 May, 2022
    Azure Monitoring Overview – Monitoring Azure Data Storage and Processing
    Azure Monitoring Overview, Exams of Microsoft, Handle Skew in Data, Microsoft DP-203, Tune Queries by Using Cache

    Every Azure product has some type of built‐in monitoring capability. Most of them have alerts, metrics, diagnostics settings, and logs, which are components of Azure Monitor. This chapter provides a detailed look into those monitoring capabilities for ADLS, Azure Synapse

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