Recommended courses on big data analysis

Warning: This article is only for study and research reference purposes, please do not use it for illegal purposes. In the previous article "Mobike Unofficial Big Data Analysis", I mentioned my data analysis of Mobike during the Spring Festival. In the following series of articles, I will further elaborate on how my crawler can efficiently crawl to of these data. Why crawl Mobike’s data? Mobike was the first shared bicycle to enter Chengdu. Every day when I get off the subway station, I can see many bicycles in the APP, but when I get there, I find that the bicycles are not there. Some cars are hidden somewhere; some cars may be behind high-rise buildings and cannot be found due to GPS errors; some cars are placed in residential areas, separated by a wall so that cyclists cannot get to them. So is there a way to obtain the data of these bicycles to analyze whether these bicycles have become zombie bicycles? Did someone deliberately put it in the community so that no one can access it? With these questions in mind, I started researching how to obtain this data. Where to get the data? If you can see the data, there is always a way to get it automatically. It’s just that the method of obtaining data determines the efficiency of obtaining data. For the task of data analysis of Mobike, this crawler

1. Mobike crawler analysis-find API

##Introduction: Warning: This article is only for learning and research reference purposes, please do not use it for illegal purposes Purpose. In the previous article "Mobike Unofficial Big Data Analysis", I mentioned my data analysis of Mobike during the Spring Festival. In the following series of articles, I will further elaborate on how my crawler can efficiently crawl to of these data. Why climb the data of Mobike? Mobike is the first shared bicycle to enter Chengdu. Every day when I get off the subway station, I can see many bicycles in the APP, but when I walk there, I find that the bicycles are not there. Some cars are hidden somewhere; some cars may be in high...

2. Using Python for big data analysis

#Introduction: It is no exaggeration to say that big data has become an indispensable part of any business communication. Desktop and mobile search provide data to marketers and companies around the world at an unprecedented scale, and with the advent of the Internet of Things, the amount of data available for consumption will grow exponentially. This consumption data is a gold mine for companies that want to better target customers, understand how people use their products or services, and collect information to improve profits.

3. Preface to Big Data Analysis Beyond Hadoop

##Introduction: This article is translated from "BIG DATA ANALYTICS BEYOND HADOOP" Translator: Wu Jingrun Proofreader: Fang Tengfei I try to leave a deep impression on people learning big data: Although Apache Hadoop is very useful, and it is a very Successful technology, but the premise of this view is somewhat outdated. Consider this timeline: MapR

#4 implemented by Google.

Impala: a new generation of open source big data analysis engine

Introduction: The original article was published in the 8th issue of "Programmer" magazine in 2013, with slight deletions. Text / Geng Yifeng Chen Guancheng ? Big data processing is a very important issue in cloud computing. Since Google proposed the MapReduce distributed processing framework, open source software represented by Hadoop has been valued and favored by more and more companies. Based on Hadoop, followed by HBase and Hive,

5.

Using Hadoop MapReduce for big data analysis

Introduction: Source: http://www.ibm.com/developerworks/cn/java/j-javadev2-15/index.html When Google released its image search feature in 2001, there were only 250 million indexed images. In less than 10 years, This massive search feature can already retrieve more than 10 billion images, with 35 hours of content uploaded to YouTube every minute. Allegedly, T

6. Big Data Analysis: Using Hunk with Hadoop or ElasticMapReduce

Introduction: Author Jonathan Allen, translator Zhang Xiaopeng Hunk is a Splunk company A relatively new product for detecting and visualizing Hadoop and other NoSQL data stores, its new version will support Amazon's Elastic MapReduce. Using Hunk with Hadoop Hadoop consists of two units. The first is a storage unit called HDFS. HDFS can

7. Microsoft releases a preview version of SQL Server 2014 to show memory Database Technology

#Introduction: At this year’s TechEd conference, Microsoft announced the first technical preview version of SQL Server 2014, which will be officially available for download this month, and the product is officially The release time is initially scheduled for the end of this year. The biggest highlight of the new version is the in-memory OLTP (On-Line Transaction Processing, online transaction processing system) at the table granularity level and the ability to provide real-time big data analysis

##8. Similar How does the Java language handle "big data analysis"? Friends with experience, please share it

Introduction: My understanding of "big data analysis" is to make some algorithm calls on existing data and return it to the matching group (such as Baidu Alliance , Taobao Alliance) So how is it handled specifically in programming projects? Is it just like my understanding? It feels like it’s not that simple... All the big data analysis I see is recruiting...

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