Tachyon and Apache Spark

•

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Meet Tachyon: an exciting new project trying to unify in-memory computing and provide a universal data-exchange layer for Hadoop ecosystem projects.

Logiciels

Tachyon and Apache Spark:
heralds of in-memory computing era.
Roman Shaposhnik
Director of Open Source @Pivotal
(Twitter: @rhatr)

Who’s this guy?
• Director of Open Source @Pivotal
• Apache Software Foundation guy (Member, VP of Apache
Incubator, committer on Hadoop, Giraph, Sqoop, etc)
• Used to be root@Cloudera
• Used to be PHB@Yahoo! (original Hadoop team)

20 minute to figure out
Hadoop vs. Spark

20 minute to figure out
Hadoop++ == Spark

Long, long time ago…
HDFS
ASF Projects
FLOSS Projects
Pivotal Products
MapReduce

In a blink of an eye
MLib
Shark
GraphX
Streaming
HDFS
Crunch Mahout
Pig
Sqoop Flume
Coordination and
workflow
management
Zookeeper
Command
Center
ASF Projects
FLOSS Projects
Pivotal Products
GemFire XD
Oozie
MapReduce
Hive
Tez
Giraph
Hadoop UI
Hue
SolrCloud
Phoenix
HBase
Spark
Impala
HAWQ
SpringXD
MADlib
Hamster
PivotalR
YARN
Tachyon

A Spark view?
HDFS
MLib
Shark
YARN
GraphX
Streaming
Tachyon
Sqoop Flume
Hadoop UI
Hue
Coordination and
workflow
management
Zookeeper
Command
Center
ASF Projects
FLOSS Projects
Pivotal Products
GemFire XD
Oozie
SolrCloud
Phoenix
HBase Spark
SpringXD

Hadoop’s view
MapReduce
server 1
server N
HDFS

Anatomy of MapReduce
HDFS mappers reducers HDFS
a b c
d a c
a 3
b 1
c 2
a 1
b 1
c 1
a 1
c 1
a 1
a 1 1 1
b 1
c 1 1

What’s wrong with MR?
Source: UC Berkeley Spark project (just the image)

This looks familiar…
$ grep –R | awk | sort …

Spark innovations
• Resilient Distribtued Datasets (RDDs)
• Distributed on a cluster
• Manipulated via parallel operators (map, etc.)
• Automatically rebuilt on failure
• A parallel ecosystem
• A solution to iterative and multi-stage apps

RDDs
warnings = textFile(…).filter(_.contains(“warning”))
.map(_.split(‘ ‘)(1))
HadoopRDD
path = hdfs://
FilteredRDD
contains…
MappedRDD
split…

Parallel operators
• map, reduce
• sample, filter
• groupBy, reduceByKey
• join, leftOuterJoin, rightOuterJoin
• union, cross

What is really happening?
MLib
Shark
GraphX
Streaming
HDFS
Crunch Mahout
Pig
Sqoop Flume
Coordination and
workflow
management
Zookeeper
Command
Center
ASF Projects
FLOSS Projects
Pivotal Products
GemFire XD
Oozie
MapReduce
Hive
Tez
Giraph
Hadoop UI
Hue
SolrCloud
Phoenix
HBase
Spark
Impala
HAWQ
SpringXD
MADlib
Hamster
PivotalR
YARN
Tachyon

But HDFS/YARN are safe?
HDFS, Ceph, S3, NAS, etc.
New
HDFS
New
YARN

Tachyon
• In-memory data-exchange layer
• A set of evolving APIs:
• filesystem
• caching
• RDDs
• Materialized views

It will be called Hadoop
MLib
Shark
GraphX
Streaming
HDFS
Crunch Mahout
Pig
Sqoop Flume
Coordination and
workflow
management
Zookeeper
Command
Center
ASF Projects
FLOSS Projects
Pivotal Products
GemFire with Tachyon
Oozie
MapReduce
Hive
Tez
Giraph
Hadoop UI
Hue
SolrCloud
Phoenix
HBase
Spark
Impala
HAWQ
SpringXD
MADlib
Hamster
PivotalR
YARN

Spark/Tachyon recap
• Is it “Big Data” (Yes)
• Is it “Hadoop” (No)
• It’s one of those “in memory” things, right (Yes)
• JVM, Java, Scala (All)
• Is it Real or just another shiny technology with
a long, but ultimately small tail (Yes and ?)

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In the past six months, the AI landscape has undergone a massive transformation, ushering in a new era of productivity with the latest in Large Language Models (LLMs) and AI technology. This deep dive unlocks how to: Create CustomGPT Models: No coding needed to tailor AI for your unique projects. Integrate your own data, including PDFs and Excel sheets, making information handling a breeze. Plus, discover how to call your own actions/integrations for even more personalized utility. Navigate Advanced Prompting: Overcome AI's memory limits and utilize Retrieval-Augmented Generation for accessing your personalized data, streamlining how you interact with AI. Stay Ahead with AI Trends: Peek into the evolving world of LLMs, featuring newcomers like Google Gemini, Anthropic Claude, Open Sora, and Twitter Grok, and understand what their advancements mean for your productivity. Witness Real-Life Transformations: Through examples and prompt demonstrations, see firsthand how these AI strategies revolutionize routine tasks, from data analysis to content creation. Learn to leverage image output and input for advanced practical use cases, adding a new dimension to your productivity toolkit. No previous coding or AI experience is needed for this talk. Stay ahead in the fast-evolving world of work. Embrace the AI revolution and transform your workflow with advanced LLM techniques. Join us to ensure you're not left behind in the productivity race.

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

VictorSzoltysek

InShot proinshot.com stands tall among its peers as the ultimate video editing app, offering simplicity, versatility, and power in one package. With its intuitive interface and comprehensive feature set, InShot caters to both beginners and seasoned editors alike. Whether you're creating content for social media, YouTube, or personal projects, InShot empowers you to unleash your creativity and transform your videos into captivating masterpieces. Join the millions of users who trust InShot https://www.proinshot.com/ for all their video editing needs and discover the difference for yourself!

Exploring the Best Video Editing App.pdf

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Unlocking the Future of AI Agents with Large Language Models

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Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...

Steffen Staab

Azure Native Qumulo scales elastically for common High Performance Compute (HPC) workloads based on application requirements for: Financial Services, Automotive, Genomics / Life Sciences, Media and Entertainment, Energy, Oil and Gas, etc. Performance can be dialed UP (and back down) much higher than the examples shown here. These slides offer a glimpse into ANQ's HPC capabilities, although at a smaller scale. We invite YOU to do your own testing (with a free ANQ trial) and work with us to test your HPC workloads in Azure.

Azure_Native_Qumulo_High_Performance_Compute_Benchmarks.pdf

ryanfarris8

In today's dynamic e-commerce landscape, the payment gateway emerges as a linchpin, ensuring smooth and secure transactions between buyers and sellers. In this discourse, we delve into the meticulous process of devising test cases tailored for scrutinizing payment gateways. Crafting precise test cases for payment gateways is a quintessential responsibility for testers operating within the service industry. This article meticulously explores pivotal scenarios integral to how to test payment gateways, coupled with essential guidelines for drafting effective test cases.

Payment Gateway Testing Simplified_ A Step-by-Step Guide for Beginners.pdf

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Craft an AI & Machine Learning Pitch with our Editable Professional PowerPoint Template. Ignite your AI & Machine Learning pitch with our cutting-edge PowerPoint template tailored for the industry. Perfect for AI conferences, investor presentations, sales pitches to tech-focused companies, training sessions, and educational programs. - 20+ editable slides: Get a variety of options to choose from for your presentation. - Time-saving solution: Download, replace text/images with a few clicks. - User-friendly customization: Easy to use and personalize. - Modern and attractive design: Captivating visuals, sleek layout. - Tailored to your requirements: Fully alterable for customization. - Well-organized slides: Complete control over content. - Thematic specificity: Reflects healthcare industry with relevant graphics. - Showcase your business idea: Communicate value proposition effectively.

AI & Machine Learning Presentation Template

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