Cloudera

AUGUST 10, 2021

We understand that migrating your data platform to the latest version can be an intricate task, and at Cloudera we’ve worked hard to simplify this process for all our customers. . We expand on this feature later in this blog. Deep Dive 2: Atlas / Kafka integration. With the release of CDP Private Cloud (PvC) Base 7.1.7,

Cloud 96

Cloud Kafka Metadata SQL 96

Confluent

APRIL 10, 2019

Previously in 3 Ways to Prepare for Disaster Recovery in Multi-Datacenter Apache Kafka Deployments , we provided resources for multi-datacenter designs, centralized schema management, prevention of cyclic repetition of messages, and automatic consumer offset translation to automatically resume applications.

Kafka 86

Kafka Metadata Java Cloud 86

Data Engineering Weekly

MAY 16, 2023

I won’t bore you with the importance of data quality in the blog. The bias toward correctness will increase the processing time, which may not be feasible when speed is a priority. Let’s talk about the data processing types. Two-Phase WAP The Two-Phase WAP, as the name suggests, follows two copy processes.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Rockset

SEPTEMBER 14, 2021

We’re introducing a new Rockset Integration for Apache Kafka that offers native support for Confluent Cloud and Apache Kafka, making it simpler and faster to ingest streaming data for real-time analytics. With the Kafka Integration, users no longer need to build, deploy or operate any infrastructure component on the Kafka side.

Kafka 52

Kafka SQL MongoDB Computer Science 52

Christophe Blefari

JANUARY 20, 2024

The Rise of the Data Engineer The Downfall of the Data Engineer Functional Data Engineering — a modern paradigm for batch data processing There is a global consensus stating that you need to master a programming language (Python or Java based) and SQL in order to be self-sufficient. Here a small benchmark between some popular formats.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Cloudera

SEPTEMBER 28, 2020

The customer also wanted to utilize the new features in CDP PvC Base like Apache Ranger for dynamic policies, Apache Atlas for lineage, comprehensive Kafka streaming services and Hive 3 features that are not available in legacy CDH versions. Support Kafka connectivity to HDFS, AWS S3 and Kafka Streams. Kafka, SRM, SMM.

Cloud 131

Cloud Kafka Professional Services Metadata 131

Cloudera

MARCH 14, 2023

In our previous DataFlow Designer blog post , we introduced you to the new user interface and highlighted its key capabilities. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.

Data Pipeline 81

Data Pipeline Designing Kafka Metadata 81

Lyft Engineering

JUNE 28, 2023

While several teams were using streaming data in their Machine Learning (ML) workflows, doing so was a laborious process, sometimes requiring weeks or months of engineering effort. In this blog post, we will discuss what we built in support of that goal and some of the lessons we learned along the way.

Machine Learning 115

Machine Learning Building Metadata Kafka 115

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.); Feel free to enjoy it.

Data Architect 87

Data Architect Certification Generalist Big Data 87

LinkedIn Engineering

DECEMBER 19, 2023

These clusters are the backbone for storing and processing extensive data volumes, empowering us to deliver essential features and services to members, such as personalized recommendations, enhanced search functionality, and valuable insights. This metadata includes the namespace, file permissions, and the mapping of data blocks to datanodes.

Big Data 92

Big Data Hadoop Metadata Data 92

Cloudera

AUGUST 10, 2021

and later, Ozone is integrated with Atlas out of the box, and entities like Hive, Spark process, and NiFi flows, will result in Atlas creating Ozone path entities. You’ll notice that Hive tables and processes are present but so are Ozone keys. Going back to Atlas, you can see the lineage has propagated from our Spark process.

Hadoop 104

Hadoop Kafka Datasets Government 104

Lyft Engineering

OCTOBER 3, 2023

Finally, as the subject of this blog post, we can assess data quality via batch compute analytics on our data warehouse, providing a comprehensive albeit slower evaluation compared to the previously mentioned methods. These flow through Kafka , our event streaming platform, before being processed by Flink , our streaming compute framework.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. Extending Atlas’ metadata model. Processes: File transfer process. ETL/DB Load process. HIVE Table.

Data Governance 93

Data Governance Government Metadata Datasets 93

Zalando Engineering

NOVEMBER 29, 2017

See Ranking Websites in Real-time with Apache Kafka’s Streams API for the first post in the series. Running Kafka Streams applications in AWS At Zalando, Europe’s leading online fashion platform, we use Apache Kafka for a wide variety of use cases. Our team at Zalando was an early adopter of the Kafka Streams API.

Kafka 40

Kafka AWS Amazon Web Services Utilities 40

Cloudera

FEBRUARY 9, 2021

A new solution integrating cloud object storage, with Cloudera’s NiFi dataflows, a Kafka datahub, and a Hive virtual warehouse in the CDW service allows businesses to take the best advantage of this public cloud trend. In the real-time layer, Kafka automatically cleans the historical events with configurable retention. Cost-Effective.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

Rockset

JULY 8, 2020

For this example, we will use Kafka. The service then pushes the geohash along with the coordinates to a Kafka topic. Rockset ingests data from this Kafka topic and updates it into a collection called locations. Orders The orders placed by a customer are stored in DynamoDB for further processing.

Kafka 40

Kafka Designing Systems Food 40

Cloudera

SEPTEMBER 30, 2021

Our recent blog discussed the four paths to get from legacy platforms to CDP Private Cloud Base. In this blog and accompanying video, we will deep dive into the mechanics of running an in-place upgrade from CDH5 or CDH6 to CDP Private Cloud Base. The overall upgrade follows a seven-step process illustrated below. Run Upgrade.

Cloud 70

Cloud PostgreSQL Metadata MySQL 70

Cloudera

JANUARY 19, 2022

These integrated data services provide fit-for-purpose solutions for different data workloads including – advanced analytics, streaming, Machine Learning and transaction processing, which will provide an end to end automated data lifecycle. Download the reports to see the detailed scores . 2021 Gartner Magic Quadrant for Cloud DBMS .

Database 87

Database Cloud Data Warehouse Data Lake 87

ProjectPro

JANUARY 24, 2023

With over 20 pre-built connectors and 40 pre-built transformers, AWS Glue is an extract, transform, and load (ETL) service that is fully managed and allows users to easily process and import their data for analytics. What is the process for adding metadata to the AWS Glue Data Catalog?

AWS 52

AWS Data Lake Scala ETL Tools 52

Cloudera

SEPTEMBER 23, 2020

Access audits are mastered centrally in Apache Ranger which provides comprehensive non-repudiable audit log for every access event to every resource with rich access event metadata such as: IP. Cloudera’s platform can support piping of audit data to HDFS, Kafka, Syslog or to SIEM systems for long-term retention and archival.

Database 81

Database Data Lake Metadata Java 81

Cloudera

DECEMBER 9, 2022

This allows developers to make changes to their processing logic on the fly while running some test data through their flow and validating that their changes work as intended. Once you have retrieved the data, NiFi stores it in a queue, which allows you to explore the content and metadata attributes of the events.

Designing 96

Designing Coding Google Cloud AWS 96

Cloudera

NOVEMBER 10, 2021

Having access to the right set of information helps users in preparing ahead of time and removing any hurdles in the upgrade process. This blog post provides CDH users with a quick overview of Ranger as a Sentry replacement for Hadoop SQL policies in CDP. Please read this blog post on Ranger RMS to learn more about this new feature.

Hadoop 74

Hadoop SQL Database Kafka 74

Cloudera

AUGUST 21, 2020

Businesses need to be able to ingest huge volumes of data from these data points as well as handle, process, and store this vast amount of data. Then they need to move to data separation so that they not only ingest the data but prepare the data so that it becomes processable.

Banking 60

Banking Kafka Cloud Storage Government 60

DoorDash Engineering

DECEMBER 5, 2023

DoorDash’s Engineering teams revamped Kafka Topic creation by replacing a Terraform/Atlantis based approach with an in-house API, Infra Service. DoorDash’s Real-Time Streaming Platform, or RTSP, team is under the Data Platform organization and manages over 2,500 Kafka Topics across five clusters.

Kafka 91

Kafka Programming Language Metadata Architecture 91

Cloudera

OCTOBER 28, 2020

The overview of both processes are as follows. Using a remote process group, we will gather all processors required to hook into the service we are ingesting from, in this case, Solr, and extract only the services we want. The first major step in this process is to convert incoming log records into records. Description.

Kafka 64

Kafka SQL Professional Services Consulting 64

LinkedIn Engineering

JANUARY 19, 2024

This multi-entity handover process involves huge amounts of data updating and cloning. Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. Push for eventual success of the request.

Recruitment 88

Recruitment Data Process Process Kafka 88

Rockset

JUNE 7, 2021

Change data capture (CDC) is the process of recognising when data has been changed in a source system so a downstream process or system can action that change. The rule of thumb is that if you are looking to build a real-time data processing system then the push approach should be used. What Is Change Data Capture?

IT 40

IT Kafka Database MongoDB 40

Rockset

MARCH 18, 2024

Flink is one of the most popular stream processing technologies, ranked as a top five Apache project and backed by a diverse committer community including Alibaba and Apple. It powers steam processing at many companies including Uber, Netflix, and Linkedin.

Cloud 64

Cloud Building Metadata Kafka 64

Netflix Tech

DECEMBER 4, 2018

We have built a custom Kafka based cross-region replication system. In our first iteration, we thought that we could use the queued up messages in Kafka to warm up the new replicas. Using Key Dumps In this approach, we dumped keys and metadata from each node from an existing replica and uploaded them to S3.

AWS 51

AWS Metadata Architecture Kafka 51

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

Process 97

Process Lambda Architecture Kafka Datasets 97

Confluent

APRIL 30, 2019

With the release of Apache Kafka ® 2.1.0, Kafka Streams introduced the processor topology optimization framework at the Kafka Streams DSL layer. This framework opens the door for various optimization techniques from the existing data stream management system (DSMS) and data stream processing literature. start(). ?

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Kafka Coding Process Bytes 90

LinkedIn Engineering

JANUARY 16, 2024

In a previous blog post, we talked about how we built our anti-abuse platform using CASAL. In this blog post, we'll go deeper into how we manage account restrictions. When we detected that a member’s intent veered into abusive territory, we set the process of imposing restrictions in motion.

Kafka 84

Kafka Relational Database Java Architecture 84

AltexSoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. What is Kafka? What Kafka is used for.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Scribd Technology

MAY 18, 2021

Streaming data from Apache Kafka into Delta Lake is an integral part of Scribd’s data platform, but has been challenging to manage and scale. We use Spark Structured Streaming jobs to read data from Kafka topics and write that data into Delta Lake tables. To serve this need, we created kafka-delta-ingest.

Kafka 52

Kafka Data Warehouse Bytes Metadata 52

Rockset

DECEMBER 22, 2020

There are many blog posts detailing how to build an Express API, I’ll concentrate on what is required on top of this to make calls to Elasticsearch. Average Star Rating We repeat the process for the average star rating but the payload we send to Elasticsearch is slightly different because this time we want an average instead of a count.

SQL 40

SQL Data MongoDB Aggregated Data 40

Zalando Engineering

JULY 31, 2016

As a member of the Zaster team (Zaster is German slang for “money”), responsible for developing payment processing components at Zalando Payments, my mission was to get in contact with other developers, companies, and speakers dealing with payment related topics. Eoin quoted Bruce Schneier: “Security is not a product, but a process”.

Finance 40

Finance Banking Java Scala 40

Confluent

MAY 29, 2019

In part 1 , we discussed an event streaming architecture that we implemented for a customer using Apache Kafka ® , KSQL from Confluent, and Kafka Streams. In part 3, we’ll explore using Gradle to build and deploy KSQL user-defined functions (UDFs) and Kafka Streams microservices. Sample repository. gradlew composeUp.

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Kafka Management Bytes SQL 95