AWS Big Data

OCTOBER 11, 2023

We introduce you to Amazon Managed Service for Apache Flink Studio and get started querying streaming data interactively using Amazon Kinesis Data Streams. Frequent materialized view refreshes on top of constantly changing base tables due to streamed data can lead to snapshot isolation errors.

Management 117

Management Metadata Analytics Dashboards 117

Cloudera

APRIL 3, 2023

Every table change creates an Iceberg snapshot, this helps to resolve concurrency issues and allows readers to scan a stable table state every time. The table metadata is stored next to the data files under a metadata directory, which allows multiple engines to use the same table simultaneously.

Data Warehouse 82

Data Warehouse Snapshot Metadata Cost-Benefit 82

Cloudera

NOVEMBER 13, 2020

Metadata Caching. If you have ever interacted with Impala in the past you would have encountered the Catalog Cache Service. As Impala’s adoption grew the catalog service started to experience these growing pains, therefore recently we introduced two new features to alleviate the stress, On-demand Metadata and Zero Touch Metadata.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

AWS Big Data

NOVEMBER 16, 2023

Performance It is not uncommon for sub-second SLAs to be associated with data vault queries, particularly when interacting with the business vault and the data marts sitting atop the business vault. Chargeback metadata Amazon Redshift provides different pricing models to cater to different customer needs.

Enterprise 96

Enterprise Data Warehouse Snapshot Cost-Benefit 96

Cloudera

SEPTEMBER 1, 2020

See the snapshot below. HDFS also provides snapshotting, inter-cluster replication, and disaster recovery. . The dashboard applications in HUE use standard Solr APIs and can interact with data indexed and stored in HDFS. Coordinates distribution of data and metadata, also known as shards. What does DDE entail?

Snapshot 71

Snapshot Unstructured Data Dashboards Interactive 71

AWS Big Data

MARCH 10, 2023

Iceberg employs internal metadata management that keeps track of data and empowers a set of rich features at scale. The Data Catalog provides a central location to govern and keep track of the schema and metadata. Additionally, you can query in Athena based on the version ID of a snapshot in Iceberg.

Data Lake 116

Data Lake Sales Data Warehouse Snapshot 116

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. Choose Create.

Data Lake 85

Data Lake Metadata Snapshot Management 85

AWS Big Data

SEPTEMBER 13, 2023

Amazon Athena is used for interactive querying and AWS Lake Formation is used for access controls. The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker. It also updates technical metadata in the AWS Glue Data Catalog.

Data Lake 103

Data Lake Data Processing Metadata Snapshot 103

AWS Big Data

FEBRUARY 1, 2023

To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. We used the same AWS Glue jobs to further transform and load the data into the required S3 bucket and a portion of extracted metadata into DynamoDB.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

NOVEMBER 29, 2023

AWS Glue interactive sessions run the SQL statements to create intermediate tables or final tables, views, or materialized views. S3FileIO --conf spark.sql.extensions=org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions" The last two lines are added for setting Iceberg configurations on AWS Glue interactive sessions.

Data Lake 116

Data Lake Management Metrics Data Warehouse 116

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 ). Take measurements 18 x DC2.

Snapshot 72

Snapshot Data Warehouse Analytics Testing 72

Alation

AUGUST 26, 2021

It includes intelligence about data, or metadata. The earliest DI use cases leveraged metadata — EG, popularity rankings reflecting the most used data — to surface assets most useful to others. Again, metadata is key. Data Intelligence and Metadata. Data intelligence is fueled by metadata.

Metadata 64

Metadata Data Governance Dashboards Software 64

AWS Big Data

JANUARY 27, 2023

The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. With unified metadata, both data processing and data consuming applications can access the tables using the same metadata. For metadata read/write, Flink has the catalog interface.

Data Lake 66

Data Lake Metadata Business Analysis Data-driven 66

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.

Data Quality 103

Data Quality Visualization Metadata Metrics 103

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. This allows the model to adapt to the latest changes in price and availability.

Data Lake 104

Data Lake Unstructured Data Management Snapshot 104

Wayne Yaddow

MARCH 14, 2025

Snapshot testing augments debugging capabilities by recording past table states, facilitating the identification of unforeseen spikes, declines, or abnormalities before their effect on production systems. Workaround: Implement custom metadata tracking scripts or use dbt Clouds freshness monitoring.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

AWS Big Data

JANUARY 17, 2024

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. Next, we create an AWS Cloud9 interactive development environment (IDE). The following are some highlighted steps: Run a snapshot query. %%sql Choose Create key pair.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

AWS Big Data

JUNE 12, 2023

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. The table can be queried using Amazon Athena , a serverless, interactive query service that enables running SQL-like queries on data stored in Amazon S3.

Management 86

Management Metadata Internet of Things Testing 86

AWS Big Data

DECEMBER 9, 2024

The metadata of an Iceberg table stores a history of snapshots. These snapshots, created for each change to the table, are fundamental to concurrent access control and table versioning. Branches are independent histories of snapshots branched from another branch, and each branch can be referred to and updated separately.

Data Quality 108

Data Quality Publishing Snapshot Data Lake 108

Cloudera

DECEMBER 3, 2024

REST Catalog Value Proposition It provides open, metastore-agnostic APIs for Iceberg metadata operations, dramatically simplifying the Iceberg client and metastore/engine integration. It provides real time metadata access by directly integrating with the Iceberg-compatible metastore. spark.sql(SELECT * FROM airlines_data.carriers).show()

Metadata 84

Metadata Data Warehouse ROI Snapshot 84

AWS Big Data

DECEMBER 19, 2024

By using features like Icebergs compaction, OTFs streamline maintenance, making it straightforward to manage object and metadata versioning at scale. Enabling automatic compaction on Iceberg tables reduces metadata overhead on your Iceberg tables and improves query performance. The Data Catalog manages the metadata for the datasets.

Data Lake 91

Data Lake IoT Metadata Testing 91

Ontotext

JANUARY 16, 2025

The second approach is much more powerful as it allows you to maintain full control over how the chat interaction works and even modify the query method input or output to suit your needs better. Use of assistant and thread metadata. So what is that metadata? Both must be strings. version Internal use only.

Metadata 52

Metadata Modeling Snapshot Interactive 52