“…What You'll Learn Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical adviceIntegrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and SparkUse StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processingUtilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processingTurbocharge Spark with Alluxio, a distributed in-memory storage platformDeploy big data in the cloud using Cloudera DirectorPerform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and SparkUnderstand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasksImplement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modelingStudy real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and MastercardWho This Book Is For BI and big data warehouse professionals interested in gaining practical and real-world insight into next-generation big data processing and analytics using Apache Kudu, Impala, and Spark; and those who want to learn more about other advanced enterprise topics…”

“…What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. …”

“…Ticketmaster: Marketing and Selling the World's Tickets John Carnahan (Ticketmaster) Learn about the solutions that Ticketmaster uses for ticket sales and marketing, including Storm for stream processing, trend prediction, and anomaly detection; and Kafka, Storm, and Hbase for real-time "n-squared" marketing. …”

“…Chaucer ci ha lasciato scritto che era grasso, che era pigro nell’alzarsi dal letto, che prediligeva le circostanze in cui poteva far la figura dello sciocco, che si pensava di lui che schivasse i suoi vicini a causa della sua mania per i libri... sembra l’autoritratto di Chesterton, che si riconosceva profondamente in questo erudito non paludato, spirito indipendente e curioso, razionale e sentimentale, autorevole e giocoso. …”

“…D’altra parte sappiamo da san Gregorio di Nissa che sua sorella, santa Macrina, nel corso della giornata era solita intonare salmodie dal Salterio; mentre sant’Efrem di Edessa, descrivendo una liturgia della Domenica delle Palme, testimonia che in chiesa le donne cantavano inni strofici con ritornelli eseguiti in modo antifonale. …”

“…El autor cree, con George Steiner, que nada puede sustitiur la presencia real del libro comentado, pero tamién sabe que casi todo el mundo mira la foto y lee la solapa antes de comprarlo. …”

Tabla de Contenidos: “…flatMapValues -- repartitionAndSortWithinPartitions -- coalesce -- foldByKey -- aggregateByKey -- combineByKey -- Advanced actions -- Approximate actions -- Asynchronous actions -- Miscellaneous actions -- Shared variable -- Broadcast variable -- Properties of the broadcast variable -- Lifecycle of a broadcast variable -- Map-side join using broadcast variable -- Accumulators -- Driver program -- Summary -- Chapter 8: Working with Spark SQL -- SQLContext and HiveContext -- Initializing SparkSession -- Reading CSV using SparkSession -- Dataframe and dataset -- SchemaRDD -- Dataframe -- Dataset -- Creating a dataset using encoders -- Creating a dataset using StructType -- Unified dataframe and dataset API -- Data persistence -- Spark SQL operations -- Untyped dataset operation -- Temporary view -- Global temporary view -- Spark UDF -- Spark UDAF -- Untyped UDAF -- Type-safe UDAF: -- Hive integration -- Table Persistence -- Summary -- Chapter 9: Near Real-Time Processing with Spark Streaming -- Introducing Spark Streaming -- Understanding micro batching -- Getting started with Spark Streaming jobs -- Streaming sources -- fileStream -- Kafka -- Streaming transformations -- Stateless transformation -- Stateful transformation -- Checkpointing -- Windowing -- Transform operation -- Fault tolerance and reliability -- Data receiver stage -- File streams -- Advanced streaming sources -- Transformation stage -- Output stage -- Structured Streaming -- Recap of the use case -- Structured streaming - programming model -- Built-in input sources and sinks -- Input sources -- Built-in Sinks -- Summary -- Chapter 10: Machine Learning Analytics with Spark MLlib -- Introduction to machine learning -- Concepts of machine learning -- Datatypes -- Machine learning work flow -- Pipelines -- Operations on feature vectors -- Feature extractors -- Feature transformers…”

“…Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark. …”

“…Método experimental, para contrastar las reacciones entre causa-efecto en la experimentación. Método estadístico, para analizar e interpretar los resultados obtenidos. …”

“…La frase del título, La rebelión de las masas, circula ya como propiedad común por haber acertado, como otras del lilbro, a presentar en forma evidente y concisa el hecho a que se refiere. …”

“…Brian Russell, Psychologist as seen on CNN, Court TV, and Fox News; Professor, University of Kansas Transform Your Personal Financial Habits and Attitudes...And Your Life! …”

“…What You Will Learn Understand modern software applications architectures Build secure microservices that can effectively communicate with other services Get to know about event-driven architectures by diving into message queues such as Kafka, Rabbitmq, and AWS SQS. Understand key modern database technologies such as MongoDB, and Amazon’s DynamoDB Leverage the power of containers Explore Amazon cloud services fundamentals Know how to utilize the power of the Go language to access key services in the Amazon cloud such as S3, SQS, DynamoDB and more. …”

“…It includes Sandeep Uttamchandani's (Intuit) talk on the three patterns to best manage data dictionaries; Simona Meriam's (Nielsen) review of the best techniques to manage Spark-Kafka consumer offsets in a relational database; Guoqiong Song's (Intel) talk on LSTM-based time series anomaly detection using Analytics Zoo for Spark and BigDL; Wolff Dobson's (Google) update on TensorFlow's best practices; and a host of other talks covering the latest in data engineering and architecture; data science, machine learning and AI; data law and ethics; data streaming and Iot; and data visualization and UX. …”

“…Highlights include: Keynote speeches, including Eva Kaili (European Parliament) on data protection and innovation; Christine Foster (Alan Turing Institute) on building the data-driven future we want to live in; and Pierre Romera (ICIJ) on the challenges of sifting through 1.4 TB of data to produce journalism's headline generating "Paradise Papers" Sessions on Data Science and Machine Learning, including Jaya Mathew and Francesca Lazzeri (Microsoft) on using deep learning models for fraud detection; Ted Dunning (MapR Technologies) on AI Rendezvous technology; Paco Nathan (O'Reilly Media) and Ihab Ilyas (University of Waterloo) on HITL/human guided machine learning; Elisa Celis (EPFL) on fairness and diversity in online social systems; and David Talby (Pacific AI) on natural language understanding at scale with spaCy and Spark NLP Sessions on Data Engineering and Architecture, including Jim Webber (Neo4j) on Neo4j's new causal clustering architecture; Dean Wampler (Lightbend) on streaming microservices with Akka Streams and Kafka Streams; Flavio Junqueira (Dell EMC) on building stream pipelines with Pravega; and Jacques Nadeau (Dremio) on using Apache Arrow for high-speed data access The Strata Business Summit, including Executive Briefings on key issues such as predictive analytics and machine learning, Cloud strategy, governance security and privacy, and AI by luminaries such as Audrey Lobo-Pulo (The Australian Treasury), Kim Nilsson (Pivigo), Martin Goodson (Evolution AI), Simon Chan (Salesforce), and Ira Cohen (Anodot) FinData Day with sessions on using big da..…”

“…Alistair Croll (Strata Chair), Tim O'Reilly (O'Reilly Media), and Susan Etlinger's (Altimeter Group) eight hour deep dive into the thorny issues of data and algorithms with help from Jana Eggers (Nara Logics), Rumman Chowdhury (Accenture), Kathy Baxter (Salesforce), Carole Piovesan (McCarthy Tétrault), and more. …”

“…Big Data and Data Science in the Cloud (30+ sessions), includes a tutorial on running data analytic workloads in the cloud; Streaming Systems and Real-time Applications (20+ sessions), includes a tutorial on streaming applications as microservices using Kafka,..…”

“…Coverage includes What IoT is and how it is transforming businesses Common IoT challenges, building blocks, and architectures Core IoT networking protocols, including the 802.15.4 and LPWA families Models for protecting security and integrity in IoT networks Simple, low-cost IoT networks for homes and small businesses IPv6 adaptations for low power and lossy IoT networks IoT management protocols, including CoAP, MQTT, and SCADA Moving processing to the edge and to the “fog” layer Using data analytics to maximize the value of IoT systems Analyzing IoT data with Hadoop, Kafka, Spark, and the Hadoop ecosystem Industry-specific techniques, smart objects, protocols, and analytic techniques IoT for utilities, the smart grid, and energy efficiency IoT for connected and self-driving cars, mass transit, and cargo transportation IoT for manufacturing: reducing cost and accelerating delivery IoT for smart and connected cities: lighting, parking, and public safety IoT for safer, more efficient oil/gas production and mining Skill Level All levels Learn How To Plan, organize, build, and deploy end-to-end IoT solutions Navigate today’s IoT product marketplace Use maturing IoT technologies to solve many business and technical problems Make sense of the full IoT protocol stack, from 802.15.4 and LPWA to IPv6 adaptations and management Archite..…”

“…Highlights include: Complete video recordings of OSCON Portland 2019’s best keynotes, tutorials, and tech sessions offering hours of material to study and absorb at your own pace and schedule Keynotes, including Adam Jacob (Chef) on the war for the soul of open source; Kay Williams (Microsoft Azure) on lessons learned building a strong Kubernetes/VSCode open source community; Adrian Cockcroft (AWS) on leveraging cloud vendors to boost open source business success; and Pete Skomoroch (Workday) on the urgent need for a new open source ML development stack Tutorials offering deep dives into open source tech like Apache Kafka, Rust, extended Berkeley Packet Filters, Spring/Spring Boot, Ethereum DApps, Jenkins 2, Vault/Kubernetes, and Kubeflow The OSCON Business Summit: sessions offering an insider’s look at the open source implementations that have the most profound impact on business with talks by open source specialists at Uber, Pacific Life, Verizon Media, The Home Depot, Baidu, the BBC, and more Open Source do-it-now sessions, including Deb Nicholson’s (Software Freedom Conservancy) whirlwind tour of what not to do when running an open source project; Russell Rutledge’s (Nike) take on how to build an open source culture at your company; and Angie Jones (Applitools) and a panel of experts from Persea Consulting, Red Hat, Magento, and ForgeRock on the best ways to build and maintain open source communities Emerging Languages and Frameworks session..…”

“…A short list of the technologies you’ll learn about include Apache Hadoop, Spark, Hive, Beam, Impala, Solr, Kudu, Mesos, Zeppelin, Akka, Cassandra, Myriad, Kafka, Apex, Druid, Python, R, graph databases, data lakes, the Trusted Analytics platform, YARN, Spark Streaming, JupyterLab, holographic data visualizations, and event-based microservices applications. …”

“…It was Neha Narkhede's (Confluent) riveting keynote on Apache Kafka and the rise of the streaming platform. It was Murat Erder's (Deutsche Bank) thought-provoking answer to how software architects should approach data in the age of Agile, big data, and the cloud. …”