@sparkslave02:~/ShellLearning/Chapter12# ./functionDemo.sh arg1./functionDemo.sharg1 args3. Shell Control Structure PreliminaryLike other programming languages, the shell has its own control structure, including for loops, while loops, until loops, if statements, and so on. This section first describes the use of a For loop, with a lot of usage for the For loop, and gives the four most commonly used for loop usages(1) for I in $ (seq 10)Root@sparkslave02: ~/shelllearning/chapter12# vim forloop.s
One: Regular expression1. The difference between a wildcard and a regular expressionWildcard characters *,? ,[]。Difference:Wildcard characters to match file namesThe regular expression is to match the string2. Meaning of ". *".: Any character*: Matches the previous character any time3. Filter out lines with a character 4. Filter out lines without a keyword 5. Show lines that begin with # 6. Display lines that are not in English at the beginning 7. Print o The row that appears two times 8. S
equivalent4 Batch ModificationCommon commands:CL modifies the current characterCW starts at the cursor and changes to the end of the wordThe CB is modified from the beginning of Word until it is at the cursorc) Change to the end of the sentence starting at the current cursorC} starts at the current cursor and changes to the end of the paragraphC (start with the current cursor and change to the beginning of the sentenceC{starts at the current cursor and changes to the beginning of the paragraphC
data position, big data engineers can say that their income has reached the top level of similar products.
As a high-paying job with less people and less money, the skill map that big data development engineers need to master is also very challenging. If you make a mind map
Transferred from: http://www.aboutyun.com/thread-7569-1-1.htmlBig Data We all know about Hadoop, but there's a whole range of technologies coming into our sights: Spark,storm,impala, let's just not come back. To be able to better architect big data projects, here to organize, for technicians, project managers, architec
speed of data, they started looking for more innovative ways to use the data.2. Are you sure you want the eggs to touch the stone?"All right, but why do I need new tools? Can't I use the original software tools to analyze big data?" We're talking about using Hadoop to arran
Computing ClustersHigh-performance computing clusters, referred to as HPC clusters. Such clusters are dedicated to providing powerful computing power that a single computer cannot provide, including numerical computation and data processing, and tends to pursue comprehensive performance. HPG is similar to supercomputing, but different, and computing speed is the first goal of Supercomputing pursuit. The fastest speed, maximum storage, the largest vol
Access to big data has been used for Hadoop for several years. Compared with the ever-changing front-end technology, I still prefer big data-this has been stir for many years, but also believe that the technology research in big
revenue growth, which are distributed in business operations, customer experience, enterprise innovation, and operation support.
So how can we realize the value of 2 trillion of the data? Dan vesset, vice president of IDC Data Analysis and Information Management Group, said that cloud-based Data Analysis and Management Solutions play an important role in promoti
Big Data
The following are the big data learning ideas compiled by Alibaba Cloud.
Stage 1: Linux
This phase provides basic courses for Big Data learning, helping you get started with big
outstanding big Data practitioners! You can donate big Data, Internet +, 18610086859, Industrial 4.0, micro-marketing, mobile internet and other free combat courses through Liaoliang Teacher's number. The complete collection of Liaoliang free videos has been released as follows: 1, "
data cleansing, but also because of the problem of Io, resulting in slowing
We must not ignore: when the data is not large, there will be slow analysis of the problem is due to the limited capacity of CPU computing.
So to synthesize my analysis, we can draw a few conclusions:
Problems with databases are limited in computing resources
In itself, there is no way to support keyword queri
Big Data projects are driven by business. A complete and excellent big data solution is of strategic significance to the development of enterprises.
Due to the diversity of data sources, data types and scales from different
systems, and development techniques. More detailed is related to: Data collection (where to collect data, if the tool is collected, cleaned, transformed, then integrated, and loaded into the data warehouse as the basis for analysis); Data access-related databases and storage architectures such as: cloud storage, Distr
-slave architecture (master-slave) is used to achieve high-speed storage of massive data through data blocks, append updates, and other methods.
3. Distributed Parallel Database
Bigtable:
Nosql:
4. Open-Source implementation platform hadoop
5. Big Dat
directories under the HDFs root directory: Hadoop FS-LSR/(2) Creating a folder in HDFs:hadoop fs-mkdir folder nameIn the root directory, create a folder called Di:(3) Uploading files to HDFs:Hadoop fs-put Local source path destination storage pathUpload a log file from the local system to the Di folder: Hadoop fs-put Test.log/di
*ps: The files that we upload through the
First, prefaceBig Data technology has been going on for more than 10 years, from birth to the present. The market has long been a company or institutions, to the vast number of financial practitioners, "brainwashing" big data the future of good prospects and trends. With the user's deep understanding of big
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