Confluent

JUNE 13, 2019

For alert rates of millions per night, scientists need a more structured data format for automated analysis pipelines. After researching formats—and reading about Confluent’s suggestion of using Avro with Kafka —we settled on using Avro, an open source, JSON-based binary format, for serializing the data in the alert messages.

Kafka 101

Kafka Bytes Data Pipeline Python 101

Edureka

FEBRUARY 7, 2023

8) Difference between ADLS and Azure Synapse Analytics Fig: Image by Microsoft Highly scalable and capable of ingesting and processing enormous amounts of data, Azure Data Lake Storage Gen2 and Azure Synapse Analytics are both available (on a Peta Byte scale). However, there are some distinctions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

DECEMBER 28, 2021

Apache Spark Streaming Use Cases There are over 3000 companies that use Spark Streaming including companies like Zendesk, Uber, Netflix, and Pinterest To create real-time telemetry analytics, Uber collects terabytes of event data every day from their mobile users. split("W+"))).groupBy((key, groupBy((key, word) -> word).count(Materialized.<String,

Architecture 52

Architecture Kafka Java Scala 52

ProjectPro

JANUARY 31, 2022

Source: Snowflake.com The Snowflake data warehouse architecture has three layers - Database Storage Layer Query Processing Layer Cloud Services Layer Database Storage Layer The database storage layer of the Snowflake architecture divides the data into numerous tiny partitions, optimized and compressed internally.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Rockset

SEPTEMBER 15, 2020

With writing and querying of data, there is always an inherent tradeoff between high write rates and the visibility of data in queries, and this is precisely what RockBench measures. Semi-structured data. Most of real-life decision-making data is in semi-structured form, e.g. JSON, XML or CSV.

Bytes 40

Bytes Database Data Warehouse Data Pipeline 40

ProjectPro

JULY 22, 2016

The desire to save every bit and byte of data for future use, to make data-driven decisions is the key to staying ahead in the competitive world of business operations. For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. Hardware Hadoop uses commodity hardware.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

NOVEMBER 22, 2021

In the event that memory is inadequate, partitions that do not fit in memory will be kept on disc, and data will be retrieved from the drive as needed. MEMORY ONLY SER: The RDD is stored as One Byte per partition serialized Java Objects. PySpark SQL is a structured data library for Spark. Discuss PySpark SQL in detail.

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

NOVEMBER 11, 2014

Spark follows a general execution model that helps in in-memory computing and optimization of arbitrary operator graphs, so querying data becomes much faster than disk-based engines like MapReduce. MEMORY_ONLY_SER: RDDs are stored as serialized Java objects, and only one-byte arrays are stored per partition.

Hadoop 40

Hadoop Scala Machine Learning Java 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