AWS Big Data

OCTOBER 3, 2023

Iceberg tables store metadata in manifest files. As the number of data files increase, the amount of metadata stored in these manifest files also increases, leading to longer query planning time. The query runtime also increases because it’s proportional to the number of data or metadata file read operations.

Optimization 117

Optimization Snapshot Data Lake Metadata 117

AWS Big Data

JUNE 27, 2024

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. To develop your disaster recovery plan, you should complete the following tasks: Define your recovery objectives for downtime and data loss (RTO and RPO) for data and metadata.

Snapshot 75

Snapshot Data Warehouse Data Processing Strategy 75

AWS Big Data

MAY 24, 2023

For more information, refer to Retry Amazon S3 requests with EMRFS. To learn more about how to create an EMR cluster with Iceberg and use Amazon EMR Studio, refer to Use an Iceberg cluster with Spark and the Amazon EMR Studio Management Guide , respectively. We expire the old snapshots from the table and keep only the last two.

Data Lake 85

Data Lake Snapshot Metadata Optimization 85

Cloudera

FEBRUARY 14, 2024

Problem with too many snapshots Everytime a write operation occurs on an Iceberg table, a new snapshot is created. A bloated metadata.json file could increase both read/write times because a large metadata file needs to be read/written every time. You could also change the isolation level to snapshot isolation.

Strategy 59

Strategy Optimization Snapshot Metadata 59

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Apache Iceberg addresses customer needs by capturing rich metadata information about the dataset at the time the individual data files are created.

Data Lake 120

Data Lake Data Processing Metadata Snapshot 120

AWS Big Data

OCTOBER 11, 2023

Frequent materialized view refreshes on top of constantly changing base tables due to streamed data can lead to snapshot isolation errors. The second streaming data source constitutes metadata information about the call center organization and agents that gets refreshed throughout the day. We use two datasets in this post.

Management 110

Management Metadata Analytics Dashboards 110

AWS Big Data

JULY 28, 2023

Tagging Consider tagging your Amazon Redshift resources to quickly identify which clusters and snapshots contain the PII data, the owners, the data retention policy, and so on. Tags provide metadata about resources at a glance. Redshift resources, such as namespaces, workgroups, snapshots, and clusters can be tagged.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

AWS Big Data

AUGUST 23, 2023

Refer to Introducing the vector engine for Amazon OpenSearch Serverless, now in preview for more information about the new vector search option with OpenSearch Serverless. To learn more about PIT capabilities, refer to Launch highlight: Paginate with Point in Time. Point in Time Point in Time (PIT) search , released in version 2.4

Snapshot 95

Snapshot Dashboards Visualization Metrics 95

AWS Big Data

JULY 3, 2023

Major market indexes, such as S&P 500, are subject to periodic inclusions and exclusions for reasons beyond the scope of this post (for an example, refer to CoStar Group, Invitation Homes Set to Join S&P 500; Others to Join S&P 100, S&P MidCap 400, and S&P SmallCap 600 ).

Snapshot 88

Snapshot Data Lake Testing Strategy 88

Cloudera

JULY 13, 2023

A range of Iceberg table analysis such as listing table’s data file, selecting table snapshot, partition filtering, and predicate filtering can be delegated through Iceberg Java API instead, obviating the need for each query engine to implement it themself. The data files and metadata files in Iceberg format are immutable.

Metadata 69

Metadata Snapshot Data Warehouse Statistics 69

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. Lake Formation permissions In Lake Formation, there are two types of permissions: metadata access and data access. Metadata access permissions allow users to create, read, update, and delete metadata databases and tables in the Data Catalog.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

AWS Big Data

JUNE 5, 2023

If you also needed to preserve the history of DAG runs, you had to take a backup of your metadata database and then restore that backup on the newly created environment. Amazon MWAA manages the entire upgrade process, from provisioning new Apache Airflow versions to upgrading the metadata database.

Snapshot 76

Snapshot Metadata Testing Data-driven 76

AWS Big Data

SEPTEMBER 13, 2023

AWS has invested in native service integration with Apache Hudi and published technical contents to enable you to use Apache Hudi with AWS Glue (for example, refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started ).

Data Lake 97

Data Lake Data Processing Metadata Snapshot 97

AWS Big Data

MARCH 27, 2023

Tags allows you to assign metadata to your AWS resources. For Filter by resource type , you can filter by Workgroup , Namespace , Snapshot , and Recovery Point. For more details on tagging, refer to Tagging resources overview. For more tagging best practices, refer to Tagging AWS resources. Choose Save changes.

Data Warehouse 85

Data Warehouse Management Snapshot Data Lake 85

AWS Big Data

FEBRUARY 1, 2023

Architecturally, we chose a serverless model, and the data lake architecture action line refers to all the architectural gaps and challenging features we determined were part of the improvements. For more details, refer to Connection Types and Options for ETL in AWS Glue. We also used AWS Lambda for data processing.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

NOVEMBER 16, 2023

Data Vault overview For a brief review of the core Data Vault premise and concepts, refer to the first post in this series. For more information, refer to Amazon Redshift database encryption. Chargeback metadata Amazon Redshift provides different pricing models to cater to different customer needs. model in Amazon Redshift.

Enterprise 90

Enterprise Data Warehouse Snapshot Cost-Benefit 90

Cloudera

JULY 14, 2023

They also provide a “ snapshot” procedure that creates an Iceberg table with a different name with the same underlying data. You could first create a snapshot table, run sanity checks on the snapshot table, and ensure that everything is in order. Hive creates Iceberg’s metadata files for the same exact table.

Snapshot 69

Snapshot Data Warehouse Metadata Testing 69

AWS Big Data

FEBRUARY 13, 2023

To do this, we required the following: A reference cluster snapshot – This ensures that we can replay any tests starting from the same state. A set of queries from the production cluster – This set can be reconstructed from the Amazon Redshift logs ( STL_QUERYTEXT ) and enriched by metadata ( STL_QUERY ).

Snapshot 67

Snapshot Data Warehouse Testing Analytics 67

AWS Big Data

AUGUST 6, 2024

At a high level, the core of Langley’s architecture is based on a set of Amazon Simple Queue Service (Amazon SQS) queues and AWS Lambda functions, and a dedicated RDS database to store ETL job data and metadata. Refer to Accessing a private Amazon MWAA environment using federated identities to implement it using your own IdP.

Cost-Benefit 96

Cost-Benefit Metadata Snapshot Metrics 96

AWS Big Data

NOVEMBER 6, 2023

You can see the time each task spends idling while waiting for the Redshift cluster to be created, snapshotted, and paused. Refer to the Configuration reference in the User Guide for detailed configuration values. To learn more about Setup and Teardown tasks, refer to the Apache Airflow documentation.

Metrics 110

Metrics Metadata Snapshot Management 110

Cloudera

JULY 13, 2022

The service provides simple, easy-to-use, and feature-rich data movement capability to deliver data and metadata where it is needed, and has secure data backup and disaster recovery functionality. In this method, you prepare the data for migration, and then set up the replication plugin to use a snapshot to migrate your data.

Snapshot 89

Snapshot Management Cost-Benefit Metadata 89

AWS Big Data

JUNE 9, 2023

Refer to Working with other AWS services in the Lake Formation documentation for an overview of table format support when using Lake Formation with other AWS services. Offers different query types , allowing to prioritize data freshness (Snapshot Query) or read performance (Read Optimized Query).

Data Lake 119

Data Lake Metadata Statistics Optimization 119

AWS Big Data

MAY 10, 2023

This event is referred to as a zonal failover. However, it’s also possible for multiple shard copies across both active zones to be unavailable in cases of two node failures or one zone plus one node failure (often referred to as double faults ), which poses a risk to availability.

Snapshot 101

Snapshot Testing Metadata Management 101

AWS Big Data

AUGUST 16, 2023

Iceberg captures metadata information on the state of datasets as they evolve and change over time. AWS Glue crawlers will extract schema information and update the location of Iceberg metadata and schema updates in the Data Catalog. For more details, refer to Creating Apache Iceberg tables. Choose Create.

Data Lake 79

Data Lake Metadata Snapshot Management 79

AWS Big Data

JANUARY 8, 2024

Refer to Amazon Kinesis Data Streams integrations for additional details. Stream Processing – An application created with Amazon Managed Service for Apache Flink can read the records from the data stream to detect and clean any errors in the time series data and enrich the data with specific metadata to optimize operational analytics.

Analytics 117

Analytics IoT Data-driven Snapshot 117

AWS Big Data

APRIL 3, 2024

By selecting the corresponding asset, you can understand its content through the readme, glossary terms , and technical and business metadata. By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes. option("header", "true").option("inferSchema",

Data Quality 96

Data Quality Visualization Metadata Metrics 96

AWS Big Data

MARCH 25, 2024

The result is made available to the application by querying the latest snapshot. The snapshot constantly updates through stream processing; therefore, the up-to-date data is provided in the context of a user prompt to the model. For more information, refer to Notions of Time: Event Time and Processing Time.

Data Lake 97

Data Lake Unstructured Data Management Snapshot 97

Cloudera

MARCH 23, 2022

The table information (such as schema, partition) is stored as part of the metadata (manifest) file separately, making it easier for applications to quickly integrate with the tables and the storage formats of their choice. Iceberg, on the other hand, is an open table format that works with open file formats to avoid this coupling.

Metadata 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

AWS Big Data

JUNE 12, 2023

Refer appendix section for more information on this feature. After the processed data is stored in Amazon S3, we create an AWS Glue crawler to create a Data Catalog table that acts as a metadata layer for the data. Refer to the first stack’s output. Refer to the first stack’s output. Refer to the first stack’s output.

Management 80

Management Metadata Testing Internet of Things 80

Cloudera

NOVEMBER 13, 2020

For a more in-depth description of these phases please refer to Impala: A Modern, Open-Source SQL Engine for Hadoop. Metadata Caching. In the previous design each Impala coordinator daemon kept an entire copy of the contents of the catalog cache in memory and had to be explicitly notified of any external metadata changes.

Optimization 142

Optimization Metadata Statistics Cost-Benefit 142

AWS Big Data

JANUARY 17, 2024

Incremental query refers to a query strategy that focuses on processing and analyzing only the new or updated data within a data lake since the last query. The key idea behind incremental queries is to use metadata or change tracking mechanisms to identify the new or modified data since the last query. /my-certs.zip

Data Lake 100

Data Lake Snapshot Big Data Data-driven 100

O'Reilly on Data

MARCH 20, 2019

Data poisoning refers to someone systematically changing your training data to manipulate your model’s predictions. Watermarking is a term borrowed from the deep learning security literature that often refers to putting special pixels into an image to trigger a desired outcome from your model. Data poisoning attacks. Watermark attacks.

Modeling 225

Modeling Machine Learning Predictive Modeling Consulting 225

Domino Data Lab

JUNE 26, 2019

On the flip side, when data scientists mark a project as complete with a description of the project conclusion, Domino also captures this metadata for project tracking and future references. All of this metadata captured can be useful for organizational learning, organize projects and help to avoid similar issues in the future. .

Data Science 65

Data Science Dashboards Metadata Snapshot 65

Cloudera

MAY 24, 2021

Second, configure a replication process to provide periodic and consistent snapshots of data, metadata, and accompanying governance policies. Once the new cluster is running, the initial data, metadata, and workload migration occurs for an application or tenant. . The side-car migration breaks down into three major phases.

Metadata 83

Metadata Testing Snapshot Strategy 83

Cloudera

MARCH 15, 2023

The record in the “outbox” table contains information about the event that happened inside the application, as well as some metadata that is required for further processing or routing. For more information refer to the Cloudera documentation. The connector generates data change event records and streams them to Kafka topics.

Data-driven 89

Data-driven Snapshot Publishing Optimization 89

AWS Big Data

MARCH 3, 2023

Let’s refer to this S3 bucket as the raw layer. Refer to Submitting EMR Serverless jobs from Airflow for additional details. For additional details on cost, refer to Amazon EMR Serverless cost estimator. For more information, refer to Introducing native Delta Lake table support with AWS Glue crawlers.

Data Lake 84

Data Lake Dashboards Metrics Metadata 84

erwin

JULY 2, 2020

a senior business process management architect at a pharma/biotech company with more than 5,000 employees, erwin Evolve was useful for enterprise architecture reference. They’re static snapshots of a diagram at some point in time. For Matthieu G., You can’t do that in things like Visio and PowerPoint. George H.,

Enterprise 122

Enterprise Modeling Metadata Data Governance 122