Monte Carlo

FEBRUARY 9, 2023

In this blog post we’ll dive into data vault architecture; challenges and best practices for maintaining data quality; and how data observability can help. architecture (with some minor deviations) to achieve their data integration objectives around scalability and use of metadata. “A What is a Data Vault model? methodology.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Netflix Tech

MAY 5, 2021

Netflix Drive relies on a data store that will be the persistent storage layer for assets, and a metadata store which will provide a relevant mapping from the file system hierarchy to the data store entities. 2 , are the file system interface, the API interface, and the metadata and data stores. A sample manifest file.

Metadata 69

Metadata Bytes Media Cloud Storage 69

Cloudera

AUGUST 14, 2020

One of the key challenges of building an enterprise-class robust scalable storage system is to validate the system under duress and failing system components. This includes, but is not limited to: failed networks, failed or failing disks, arbitrary delays in the network or IO path, network partitions, and unresponsive systems.

Hadoop 96

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Rock the JVM

AUGUST 9, 2022

For a more concrete example, we are going to write a program that will parse markdown files, extract words identified as tags, and then regenerate those files with tag-related metadata injected back into them. FileInputStream In our example later, we are going to process blog posts to parse tag meta-data.

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Confluent

JULY 1, 2019

Apache Kafka ® is a distributed system. When a client (producer/consumer) starts, it will request metadata about which broker is the leader for a partition—and it can do this from any broker. This is the metadata that’s passed back to clients. Using -L , you can see the metadata for the listener to which you connected.

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DoorDash Engineering

JANUARY 23, 2024

Although that process started with a limited set of configurations, the old system struggled to keep up with DoorDash’s growth across new verticals. Additionally, the current system operates with a limited set of features, reducing the speed with which new capabilities and experiments can be launched.

Architecture 74

Architecture Metadata Bytes Systems 74

Tweag

APRIL 19, 2023

Most training pipelines and systems are designed to handle fairly small, sub-megapixel images. In this blog post, I will explain the underlying technical challenges and share the solution that we helped implement at kaiko.ai , a MedTech startup in Amsterdam that is building a Data Platform to support AI research in hospitals.

Medical 60

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Confluent

MAY 29, 2019

If you want to follow along and execute all the commands included in this blog post (and the next), you can check out this GitHub repository , which also includes the necessary Docker Compose functionality for running a compatible KSQL and Confluent Platform environment using the recently released Confluent 5.2.1. Sample repository.

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ProjectPro

NOVEMBER 22, 2021

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. To define the columns, PySpark offers the pyspark.sql.types import StructField class, which has the column name (String), column type (DataType), nullable column (Boolean), and metadata (MetaData).

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Snowflake provides data warehousing, processing, and analytical solutions that are significantly quicker, simpler to use, and more adaptable than traditional systems.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Confluent

APRIL 30, 2019

This framework opens the door for various optimization techniques from the existing data stream management system (DSMS) and data stream processing literature. addSink(" SinkProcessor" , "output" , "MappingProcessor" ); System. build(properties); System. With the release of Apache Kafka ® 2.1.0, println(builder.

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ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. RDBMS is a part of system software used to create and manage databases based on the relational model. FSCK stands for File System Check, used by HDFS.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Dataquest

NOVEMBER 4, 2019

In this blog post, we’ll use data from web server logs to answer questions about our visitors. If you’re unfamiliar, every time you visit a web page, such as the Dataquest Blog , your browser is sent data from a web server. To host this blog, we use a high-performance web server called Nginx. PingdomPageSpeed/1.0

Data Pipeline 52

Data Pipeline Python Building Raw Data 52

ProjectPro

JULY 6, 2016

This is just a hypothetical case that we are talking about and if you prepare well, you will be able to answer any HBase Interview Question, during your next Hadoop job interview, having read ProjectPro Hadoop Interview Questions blogs. HBase system consists of tables with rows and columns just like a traditional RDBMS.

Hadoop 40

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ProjectPro

JUNE 29, 2021

This blog brings you the most popular Kafka interview questions and answers divided into various categories such as Apache Kafka interview questions for beginners, Advanced Kafka interview questions/Apache Kafka interview questions for experienced, Apache Kafka Zookeeper interview questions, etc.

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Rockset

FEBRUARY 14, 2020

tesla-integration" You’ll notice in the results that not only will you see the lat and long you sent to the Kafka topic but some metadata that Rockset has added too including an ID, a timestamp and some Kafka metadata, this can be seen in Fig 2. seconds which is perfectly acceptable for any front end system.

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nodeSWAT

JUNE 21, 2016

The following blog post is a long one, but hang in there, it will be worth it. Did you know that by default, NPM keeps all the packages and metadata it ever downloads in its cache folder indefinitely? link] So what happens is that when you install things, NPM will store the tarballs and metadata into the packages folder.

Metadata 52

Metadata Google Cloud Coding Bytes 52