learn big data from scratch

From the original Big Data Liaoliang video Video 23 speakvar triple = (x:double) = 3 *x> triple:double = Double =Array (3.14,1.42, 2.0). Map ((x:double) = 3 * x)> res0:array[double] = Array (9.42, 4.26, 6.0)Array (3.14,1.42, 2.0). map{(x:double) = 3 * x}> res1:array[double] = Array (9.42, 4.26, 6.0)Defaddby (factor:double) = (x:D ouble) =>factor + x> Addby: (factor:double) Double = Doublevar total =addby (5

Https://www.ibm.com/developerworks/cn/opensource/os-cn-apache-flink/index.htmlDevelopment of the Big Data computing engineWith the rapid development of big data in recent years, there have been many popular open source communities, including Hadoop, Storm, and later Spark, all with their own dedicated application scena

produces a SQL script file that contains the commands necessary to recreate the database from scratch, create TABLE insert, and so on. Statements that are backed up using mysqldump: mysqldump -u root 数据库名>备份文件名; #备份整个数据库 mysqldump -u root 数据库名 表名字>备份文件名; #备份整个表 We try to back up the entire database Mysql_shiyan, name the backup file bak.sql, Ctrl + Z to quit MySQL, and then use the statement: mysqldump -u root mysql_shiyan > bak.sql; Using the

Memcache big data storage problem huangguisu Memcached stores the maximum data size of a single item within 1 MB. If the data exceeds 1 MB, false is returned for both set and get access, which causes performance problems. We used to cache the data in the ranking table. Becau

Memcache big data storage problem huangguisu Memcached stores the maximum data size of a single item within 1 MB. If the data exceeds 1 MB, false is returned for both set and get access, which causes performance problems. We used to cache the data in the ranking table. Becau

in HDFs into a relational database.Oozie.Apache Oozie is a scalable, reliable, and extensible workflow Scheduling system for managing Hadoop jobs. Oozie Workflow Job is an active directed acyclicalGraphs (DAGs). The Oozie Coordinator job is triggered by periodic Oozie workflow jobs, which typically depend on the time (frequency) and the availability of the data. Oozie andThe rest of the Hadoop stack is used in conjunction with out-of-the-box support

Younger brother did not work on the big website, but want to accumulate some big data, high concurrency website practical experience, in addition to change work, there are other ways of learning? Who's the big Brother pointing out? Reply content: Younger brother did not work on the

1 Preface For a long time, I have always asked myself what I want to learn and whether it will help my current job? Yes, there are too many new things in the computer industry. If I talk about them all, I am also confused. It must be irrational and time-consuming, it is very likely that you have not learned deeply. For massive data, the so-called big

Financial-level big data cloud services are not that unattainable, For non-insiders, the IT system of financial institutions seems very mysterious. In the eyes of those who have seen more technology movies, the IT system is like this: → A inaccessible place that goes deep into underground or mountain data centers; → Multi-Channel Optical Cables, satellite communi

gain an in-depth understanding of the customer's browsing habits, and analyze the customer's behavior habits. When the user gives up the shopping cart, the user can also organize policies based on the situation, for example, after analysis, you can know what kind of email marketing is most effective. Historical purchase data:The customer's previous purchase data is very valuable. This data can predict the

, the risk is very big, the return is very low, not every company can play;6, machine learning needs iterative iteration;7, hard disk reading cost is very high;8. The two-direction of data and model;9. ML Machine Learning10, Spark:faster MapR on Data Parallel;11, Graphlab,petuum, semi-synchronous;12, SAP based on the parallelization of the structure;1, read the h

First, reviewLet's review what we've said in the last few chapters. Summarized as follows: "Janet: Looking at the IT architecture in the Big Data era (1) Industry Message Queuing comparison" Janet: Looking at the IT architecture in the Big Data Era (2) Message Queuing r

Trait similar to interface in Java but there are differences trait can inherit trait and in trait can write abstract methods, you can also implement the method instance as followsTrait Walk{Def walk () {}}Class Person extends Walk{println ("Hello-----")Override Def walk () {println ("Let's Have a Walk")}}Trait Run extends Walk{def run (){println ("Gofor A walk and run around")}}Object Hellotrait {def main (args:array[string]): Unit = {Val tt = Newperson with RunTt.run ()}}Printing results:Hello-

Child class inherits the parent class to complete the parent class parameter of the Fill class person (Val name:string, Val age:int) {println ("Father ' s constructor")Val class = "First Class"def read = "Ten hours"Override def toString = "I am a Goodperson"}Class Stu (Namestu:string,agestu:int,val sex:string) Extendsperson (Namestu,agestu){println ("Son ' s constructor")Override Val Class = "I ' m a student in FirstClass"Override def toString = "I am a good student"}Object Uni {def main (args:a

The original video tutorial multiple inheritance is relatively good understanding, the main AOP programming process needs to understand the following is a specific example:Trait Action{def doAction}Trait Beforeafter extends Action{Abstract override Def DoAction{println ("Before ...")Super.doactionprintln ("After ...")}}Class Dog extends Action{Override Def DoAction =println ("Barking ...")}Object TESTAOP {def main (args:array[string]): Unit = {Val dog = new dog with BeforeafterDog.doaction}The r