Databricks is a company founded by the creators of Apache Spark, that aims to help clients with cloud-based big data processing using Spark. Databricks grew out of the AMPLab project at University of California, Berkeley that was involved in making Apache Spark, a distributed computing framework built atop Scala. Its co-founders are: Ali Ghodsi, CEO, University of California, Berkeley adjunct professor and co-founder, Andy Konwinski, Ion Stoica, Executive Chairman, University of California, Berk...

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Databricks
Databricks
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  • Apache Spark’s Structured Streaming with Amazon Kinesis on Databricks
    On July 11, 2017, we announced the general availability of Apache Spark 2.2.0 as part of Databricks Runtime 3.0 (DBR) for the Unified Analytics Platform. To augment the scope of Structured Streaming on DBR, we support AWS Kinesis Connector as a source (to read streams from), giving developers the freedom to do three things. First, […] The post Apache Spark’s Structured Streaming with Amazon Kinesi...
Databricks
Databricks
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Databricks
Databricks
Blog Post

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  • On-Demand Webinar and FAQ: Accelerate Data Science with Better Data Engineering on Databricks
    On July 13th, we hosted a live webinar — Accelerate Data Science with Better Data Engineering on Databricks. This webinar focused on the use of PySpark in transforming petabytes of data for ad-hoc analysis and generating downstream queries. In particular, we covered: Transforming TBs of data with RDDs and PySpark responsibly Using the JDBC connector […] The post On-Demand Webinar and FAQ: Accelera...
Databricks
Databricks
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  • Jumpstart on Apache Spark 2.2 on Databricks
    In this introductory part lecture and part hands-on workshop, you’ll learn how to apply some of these new APIs using Databricks Community Edition. In particular, we will cover the following areas: Agenda: • Overview of Spark Fundamentals & Architecture • What’s new in Spark 2.x • Unified APIs: SparkSessions, SQL, DataFrames, Datasets • Introduction to DataFrames, Datasets and Spark SQL • In...
Databricks
Databricks
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  • Jump Start on Apache® Spark™ 2.x with Databricks
    Apache Spark 2.0 and subsequent releases of Spark 2.1 and 2.2 have laid the foundation for many new features and functionality. Its main three themes—easier, faster, and smarter—are pervasive in its unified and simplified high-level APIs for Structured data. In this introductory part lecture and part hands-on workshop, you’ll learn how to apply some of these new APIs using Databricks Community E...
Databricks
Databricks
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  • Build, Scale, and Deploy Deep Learning Pipelines with Ease
    Deep Learning has shown a tremendous success, yet it often requires a lot of effort to leverage its power. Existing Deep Learning frameworks require writing a lot of code to work with a model, let alone in a distributed manner. This webinar is the first of a series in which we survey the state of Deep Learning at scale, and where we introduce the Deep Learning Pipelines, a new open-source packa...
Databricks
Databricks
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  • A Tale of Three Tools: Kubernetes, Jsonnet, and Bazel
    As part of the long term goal to contribute to the Kubernetes ecosystem of components and tools, at Databricks we’ve implemented a Python tool called kubecfg to allow us to succinctly describe deployment configurations in a highly modular way. In its current version, kubecfg will compile Jsonnet files using the Python _jsonnet library from Google, accepting command-line arguments to override spec...
Databricks
Databricks
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  • Breaking the “curse of dimensionality” in Genomics using “wide” Random Forests
    This is a guest blog from members of CSIRO’s transformational bioinformatics team in Sydney, Australia. CSIRO, Australia’s government research agency, is in the top 1% of global research institutions with inventions like fast WiFi, the Hendra virus vaccine, and polymer banknotes. It is their technical account of a scalable VariantSpark toolkit for genomic analysis at […] The post Breaking the “cur...
Databricks
Databricks
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  • Integrating Apache Airflow with Databricks
    This blog post is part of our series of internal engineering blogs on Databricks platform, infrastructure management, integration, tooling, monitoring, and provisioning. Today, we are excited to announce native Databricks integration in Apache Airflow, a popular open source workflow scheduler. This blog post illustrates how you can set up Airflow and use it to trigger […] The post Integrating Apac...
Databricks
Databricks
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  • Serverless Continuous Delivery with Databricks and AWS CodePipeline
    Two characteristics commonly mark many companies’ success. First, they quickly adapt to new technology. Second, as a result, they gain technological leadership and, in turn, greater market share. Organizations that can quickly turn insight into action maintain huge advantages over their competition. The key to exploiting analytics in an agile and iterative fashion is a […] The post Serverless Cont...
Databricks
Databricks
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  • Benchmarking Big Data SQL Platforms in the Cloud
    Performance is often a key factor in choosing big data platforms. Given SQL is the lingua franca for big data analysis, we wanted to make sure we are offering one of the most performant SQL platforms in our Unified Analytics Platform. In this blog post, we compare Databricks Runtime 3.0 (which includes Apache Spark and […] The post Benchmarking Big Data SQL Platforms in the Cloud appeared first on...
Databricks
Databricks
Blog Post

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  • Introducing Apache Spark 2.2
    Today we are happy to announce the availability of Apache Spark 2.2.0 on Databricks as part of the Databricks Runtime 3.0. This release marks a major milestone for Structured Streaming by marking it as production ready and removing the experimental tag. In this release, we also support for arbitrary stateful operations in a stream, and […] The post Introducing Apache Spark 2.2 appeared first on Da...
Databricks
Databricks
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  • Accelerating Data Science with Better Data Engineering on Databricks
    Whether you’re processing IoT data from millions of sensors or building a recommendation engine to provide a more engaging customer experience, the ability to derive actionable insights from massive volumes of diverse data is critical to success. MediaMath, a leading adtech company, relies on Apache Spark to process billions of data points ranging from ads, user cookies, impressions, clicks, and ...
Databricks
Databricks
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  • Deep Learning to Big Data Analytics on Apache Spark Using BigDL with Xianyan Jia and Yuhao Yang
    With the continued success of deep learning techniques, there’s been a rapid growth in applications for perception in many modalities, such as image classification, object detection and speech recognition. In response, Intel’s BigDL is an open source distributed deep learning framework for Apache Spark that includes rich deep learning support and Intel Math Kernel Library acceleration, allowing u...
Databricks
Databricks
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Databricks
Databricks
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  • Spark Machine Learning: Adding Your Own Algorithms and Tools with Holden Karau and Seth Hendrickson
    Apache Spark’s machine learning (ML) pipelines provide a lot of power, but sometimes the tools you need for your specific problem aren’t available yet. This talk introduces Spark’s ML pipelines, and then looks at how to extend them with your own custom algorithms. By integrating your own data preparation and machine learning tools into Spark’s ML pipelines, you will be able to take advantage of u...
Databricks
Databricks
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  • Analytics at Scale with Apache Spark on AWS with Jonathan Fritz
    Organizations from small startups to large enterprises are rapidly adopting Apache Spark on Amazon EMR in Amazon Web Services (AWS) to run streaming analytics, data science, machine learning, and batch processing workloads. These customers can quickly create big data architectures within minutes, and decouple compute and storage with Amazon S3 as a highly scalable, durable, and secure data lake, ...
Databricks
Databricks
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Databricks
Databricks
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  • 4 SQL High-Order and Lambda Functions to Examine Complex and Structured Data in Databricks
    A couple of weeks ago, we published a short blog and an accompanying tutorial notebook that demonstrated how to use five Spark SQL utility functions to explore and extract structured and nested data from IoT Devices. Keeping with the same theme, I want to show how you can put to a wide use of the […] The post 4 SQL High-Order and Lambda Functions to Examine Complex and Structured Data in Databrick...
Databricks
Databricks
Blog Post

New blog articles detected.

  • Declarative Infrastructure with the Jsonnet Templating Language
    This blog post is part of our series of internal engineering blogs on Databricks platform, infrastructure management, tooling, monitoring, and provisioning. At Databricks engineering, we are avid fans of Kubernetes. Much of our platform infrastructure runs within Kubernetes, whether in AWS cloud or more regulated environments. However, we have found that Kubernetes alone is not […] The post Declar...
Databricks
Databricks
Blog Post

New blog articles detected.

  • Parallelizing Large Simulations with Apache SparkR on Databricks
    This blog post is a joint engineering effort between Shell’s Data Science Team (Wayne W. Jones and Dennis Vallinga) and Databricks (Hossein Falaki). Introduction Apache Spark 2.0 introduced a new family of APIs in SparkR, the R interface to Apache Spark to enable users to parallelize existing R functions. The new dapply, gapply and spark.lapply […] The post Parallelizing Large Simulations with Apa...
Databricks
Databricks
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  • Web-Scale Graph Analytics with Apache® Spark™
    Graph analytics has a wide range of applications, from information propagation and network flow optimization to fraud and anomaly detection. The rise of social networks and the Internet of Things has given us complex web-scale graphs with billions of vertices and edges. However, in order to extract the hidden gems within those graphs, you need tools to analyze the graphs easily and efficiently. ...
Databricks
Databricks
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  • Integrating Deep Learning Libraries with Apache Spark
    The combination of deep learning with Apache Spark has the potential to make a huge impact. Joseph Bradley and Xiangrui Meng share best practices for integrating popular deep learning libraries with Apache Spark. Rather than comparing deep learning systems or specific optimizations, Joseph and Xiangrui focus on issues that are common to many deep learning frameworks when running on a Spark cluste...
Databricks
Databricks
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  • Accelerating Innovation with Unified Analytics
    Today at the 10th Spark Summit, Databricks CEO & Co-founder revealed Databricks Serverless, a new initiative to offer serverless computing for complex data science and Apache Spark workloads. Databricks Serverless is the first product to offer a serverless API for Apache Spark, greatly simplifying and unifying data science and big data workloads for both end-users and DevOps.
Databricks
Databricks
YouTube Video

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  • Accelerating Innovation with Unified Analytics - Ali Ghodsi & Greg Owen 2
    Today at the 10th Spark Summit, Databricks CEO & Co-founder revealed Databricks Serverless, a new initiative to offer serverless computing for complex data science and Apache Spark workloads. Databricks Serverless is the first product to offer a serverless API for Apache Spark, greatly simplifying and unifying data science and big data workloads for both end-users and DevOps.
Databricks
Databricks
Blog Post

New blog articles detected.

  • Analysing Metro Operations Using Apache Spark on Databricks
    This is a guest blog from EY Advisory Data & Analytics team, who have been working with Sporveien in Oslo building a platform for metro analytics using Apache Spark on Databricks. Sporveien is the operator of the Oslo Metro, a municipally owned Metro network supplying the greater Oslo area with public transportation since 1898. Today, […] The post Analysing Metro Operations Using Apache Spark on D...
Databricks
Databricks
Blog Post

New blog articles detected.

  • Five Spark SQL Utility Functions to Extract and Explore Complex Data Types
    For developers, often the how is as important as the why. While our in-depth blog explains the concepts and motivations of why handling complex data types and formats are important, and equally explains their utility in processing complex data structures, this blog post is a preamble to the how as a notebook tutorial. In this […] The post Five Spark SQL Utility Functions to Extract and Explore Com...
Databricks
Databricks
Blog Post

New blog articles detected.

  • 10th Spark Summit Sets Another Record of Attendance
    We have assembled a selected collage of highlights from Databricks’ speakers at our 10th Spark Summit, a milestone for Apache Spark community and users. Shortly, the coverage of all sessions and slides will be available on the Spark Summit 2017 website. Day One: Developer Day Expanding Apache Spark Use Cases in 2.2 and Beyond Apache […] The post 10th Spark Summit Sets Another Record of Attendance ...

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