Ascend.io

MAY 19, 2023

Moore in his book, Crossing the Chasm ) rush to build and launch hundreds of new tools to the market (Stage 2). In the data world, this disruption manifested in the form of cloud computing with technologies such as Redshift, Snowflake, and Spark. What is the post-modern data stack? Let’s review it briefly.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

ProjectPro

NOVEMBER 22, 2021

PySpark runs a completely compatible Python instance on the Spark driver (where the task was launched) while maintaining access to the Scala-based Spark cluster access. StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. sports activities).

Hadoop 52

Hadoop Python Datasets Metadata 52

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

ProjectPro

JANUARY 31, 2023

Every map/reduce action carried out by the Hadoop framework on the data nodes has access to cached files. As a result, the data files in the task assigned can access the cache file as a local file. Why is HDFS only suitable for large data sets and not the correct tool for many small files?

Big Data 52

Big Data Hadoop AWS Relational Database 52

Netflix Tech

OCTOBER 27, 2020

Netflix Scheduler is built on top of Meson which is a general purpose workflow orchestration and scheduling framework to execute and manage the lifecycle of the data workflow. Bulldozer makes data warehouse tables more accessible to different microservices and reduces each individual team’s burden to build their own solutions.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Cloudera

JANUARY 11, 2021

In a multi-tenant environment, many users need to access the same data sources. Experimental and production workloads access the same data without users impacting each others’ SLAs. Cloudera Data Warehouse has two high-performance, massively parallel processing (MPP) query engines — Impala and Hive LLAP.

Data Warehouse 62

Data Warehouse Pharmaceutical Data Lake BI 62

Zalando Engineering

SEPTEMBER 8, 2021

Feels like Zalando - We want a consistent and accessible look and feel for all user journeys and ability to experiment with design fast, across multiple user flows. Renderer State: Renderers have access to a local Renderer State. Renderers have access to Zalando’s GraphQL Mutation APIs which allows remote data to be modified.

Engineering 52

Engineering Computer Science Data Schemas Coding 52

Confluent

APRIL 30, 2019

When building a topology with the Processor API, you explicitly name each processing node in the topology, and also provide the name(s) of all of its parent nodes (the only exception are source nodes, which do not have any parents). .< build(properties); final KafkaStreams streams = new KafkaStreams(topology, properties); streams.

Kafka 89

Kafka Coding Process Bytes 89

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Hive requires a well-defined Schema. Language It is a procedural data flow language. Hcatalog can be used to share data structures with external systems.

Hadoop 40

Hadoop Metadata SQL Database 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40