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More Cash for DataRobot Along with ML Ops Tool

High-flying enterprise AI specialist DataRobot announced another huge funding round along with a machine learning platform for managing predictive models that combines internally developed monitoring framework with so-called ML Ops tools acquired earlier this year. Boston-based DataRobot said Tuesday (Sept. 17) it has added another $206 million to its venture capital war chest, bringing its investment total through seven funding rounds to $431 million. It announced a $100 million Series D funding round last October. Alliance Bernstein PCI,...

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Talking about DAG Task Decomposition and Shuffle RDD

1. Dag Scheduler Analysis The Dag Scheduler function is mainly responsible for the decomposition and Task submission of each stage of RDD. Stage decomposition starts from finalStage, which triggers the Task scheduling process, and retrieves the parent stage. If the parent stage does not commit the Task, the missing parent stage is submitted in a loop. Each stage has a concept of a parent RDD that creates multiple tasks (Tasks) based on the number of partitions. Task scheduling is actually accomplished through Task Scheduler Imp. Task...

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Apache Flink Zero Foundation Initial Flink Data Stream Programming

Data sources can be created by Stream Execution Environment. addSource (sourceFunction). Flink also provides some built-in data sources for easy use, such as readTextFile(path) readFile(), and of course, it can also write a custom data source (by implementing the SourceFunction method, but can not be implemented in parallel). That's ok. Or implement an interface Parallel Source Function that can be implemented in parallel or inherit Rich Parallel Source Function) Introduction Start with a simple introduction to building a DataStream...

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Deep Understanding of Spark 2.1 Core: TimSort Principle and Source Code Analysis

In the blog Deep Understanding of Spark 2.1 Core (X): Principles and Source Code Analysis of Shuffle Map End We mentioned that: Sort and others are used to sort the data, and TimSort is used. In this blog post, let's take a deeper look at Tim Sort Understanding timsort After watching the video, you may find that TimSort and MageSort are very similar. Yes, you'll find that it's just a series of improvements to merge sort. Some of them are very smart, while others are quite straightforward. These large and small improvements aggregate to...

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Spark integrates Kafka and manually maintains offset

Spark Integrates Kafka's Two Patterns In development, we often use SparkStreaming to read and process data in kafka in real time. After version 1.3 of SparkStreaming, KafkaUtils provides two methods to create DStream: Receiver reception: KafkaUtils.createDstream There is a Receiver as a resident Task running in Executor waiting for data, but a Receiver is inefficient, need to open multiple, then manually merge data, and then process, very troublesome, and the Receiver machine hangs up, part of the data will be lost, need to open WAL...

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Spark from zero to Spark API In Java8

                          Spark API In  Java8 1. map, flatMap map is easy to understand. It passes an element of the source JavaRDD into the call method and returns one by one after the algorithm to generate a new JavaRDD. map Sample Code List<Integer> list = Arrays.asList(1, 2, 3); System.out.println(list.size()); JavaRDD<Integer> listRDD = sc.parallelize(list); JavaRDD<Integer> nameRDD = listRDD.map(n -> { return n * n; }); nameRDD.foreach(f -> { System.out.println("n Square=" + f); }); Run...

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Baidu In-Memory Databases Add Intel Optane

Chinese e-commerce giant Baidu is building a new platform based on Intel Corp.’s Optane DC persistent memory as a means of upgrading search engine results delivered by its in-memory databases used to feed its streaming data services. The partners also published a case study this week detailing the restructuring of its in-memory database using Optane memory technology introduced last year. Baidu said it plans to shift its in-memory databases to an Optane-only configuration as a replacement for DRAMs. Baidu said combination of Optane and...

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10 Hours Start Big Data: Chapter 6 - Hadoop Project Practice

Overview of User Behavior Log User Behavior Log: All behavioral data (access, browse, search, click, etc.) of the user each time he visits the website User Behavior Trajectory, Traffic Log Why Log User Access Behavior Visits to Web pages Viscosity of Web Sites Recommendation How logs are generated     nginx     ajax Content of User Behavior Log     ip Account number Access time zone Client Browser Access module How to Jump Wait a minute. Log data content: 1) System attributes accessed: operating system, browser, etc. 2) Access...

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Patterns Matching and Sample Classes of spark Notes

Level has a very powerful pattern matching mechanism, which can be applied to many occasions, such as switch statements, type checking and so on. Level also provides sample classes to optimize pattern matching, which can quickly match.1.1. Matching string package cn.itcast.cases import scala.util.Random   object CaseDemo01 extends App{   val arr = Array("hadoop", "zookeeper", "spark")   val name = arr(Random.nextInt(arr.length))   name match {     case "hadoop"    => println("Large Data Distributed Storage and Computing...

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Common operations of ArrayList and LinkedList

The main contents of this paper are as follows: 1. Common operations of ArrayList 2. A Brief Introduction to Random Numbers 3. Comparisons of Java Custom Equivalence 4. A Brief Introduction to Iterators 5. The relationship between Iterable and foreach 6. Common operations of LinkedList 7. A brief description of instanceOf 8.ArrayList exercise (shuffling) 9.LinkedList Common Operational Exercises1. Common ArrayList operations: (1) Construction method ArrayList(); constructs an empty sequential table with default capacity ArrayList(int...