MongoDB and market research of IT vacancies

Have you ever analyzed a job?
 
 
The question was asked, in what technologies is the labor market most demanding at the moment? A month ago? A year ago?
 
 
How often do new Java developer vacancies open in a certain area of ​​your city and how actively do they close?
 
 
In this article I will tell you how you can achieve the desired result and build a report system on the topic of interest to us. Go!
 
 
MongoDB and market research of IT vacancies

 
Source
 
Headhunter.ru
 
Probably, many of you are familiar and even used a resource like Headhunter.ru ...
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Is the problem of injections in JavaScript relevant?

Is the problem of injections in JavaScript relevant?In the old days, when web development was based on the fact that server applications sent queries to relational databases and issued HTML output, there was often a code like this:
 
 
//WARNING: Bad example!
function popup (msg: string): string {
return " " + msg + " ";
}

 
or such:
 
 
//WARNING: Bad example!
function getName (login: string): string {
return "SELECT name FROM users WHERE login =" "+ login +" "";
}

 
Since then, we have learned to use safer approaches.
 
 
Widely used tools such as templating and binding parameters. Today, you can rarely find dangerous string concatenation.
 
 
In th...
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Theory and practice of using HBase

Theory and practice of using HBaseGood afternoon! My name is Danil Lipova, our team at Sbertech started using HBase as a data warehouse. In the course of his study, experience accumulated, which he wanted to systematize and describe (we hope that many will be useful). All the experiments below were carried out with versions of HBase ???-cdh??? and ???-cdh???-beta1.
 
 
 
General architecture
 
Write data to HBASE
 
Reading data from HBASE
 
Caching of the data
 
Batch processing of MultiGet /MultiPut data
 
Strategy for breaking tables into regions (spiliting)
 
Fault Tolerance, Compactification and Locality of Data
 
Settings ...
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Migration of ElasticSearch data lossless

Migration of ElasticSearch data lossless
 
Academic design of the data warehouse recommends keeping everything in a normalized form, with links between. Then the rolling of changes in relational mathematics will give a reliable storage with support for transactions. Atomicity, Consistency, Isolation, Durability - that's all. In other words, the storage is specially built for secure data updates. But it is not optimal for searching, especially with a broad gesture on tables and fields. We need indices, many indices. The volumes expand, the recording slows down. SQL LIKE is not indexed, but JOIN GROUP BY sends meditation to the query scheduler.
 
The i...
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Where is his button ?! As a simple person to download data from Kibana and Elasticsearch and do not strain the developers

Where is his button ?! As a simple person to download data from Kibana and Elasticsearch and do not strain the developersElasticsearch, Kibana and Logstash (ELK) are an excellent set of tools for collecting and visualizing large amounts of data.
 
 
Logs, logs, events - all of this is quite easy to gather, map and displayed in a single tool. Logstash stores data, Elasticsearch stores it, and Kibana displays it in graphical form.
 
 
With all the power of this bundle, of course, there are tasks that can not be realized through the built-in capabilities.
 
 
For example, Kibana perfectly displays data within a single table (index), but as soon as it comes to combining different indexes into one sample, it helplessly ...
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JOIN in NoSQL databases

In this message, we will look at ways to connect collections in NoSQL databases mongodb, arangodb, orientdb and rethinkdb (in addition to being a NoSQL database, they also have a free version with a fairly loyal license). In relational databases, similar functionality is implemented using SQL JOIN. Despite the fact that CRUD operations in NoSQL databases are very similar and differ only in details, for example, in one database, create ({}) is used to create an object, on the other - insert ({}), and in third - save ({}), - the implementation of a sample of two or more collections in each database ...
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Applications for Tarantool. Part 3. Testing and launching

The application for Tarantool is, in essence, a set of stored procedures used as an API. The data is processed on the storage side, which can significantly improve performance. However, support for stored procedures can turn into a nightmare.
 
Can. But not today.
 
Today we will consider the issues of ensuring the quality of the application. In particular, let's talk about testing, understand how to launch in production, how to use connectors, and also talk about the intricacies of migration of the data schema.
 
Applications for Tarantool. Part 3. Testing and launching ...
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Designing Schemaless of the Uber Engineering data warehouse using MySQL

Designing Schemaless, Uber Engineering's Scalable Datastore Using MySQL


 
By Jakob Holdgaard Thomsen
 
January 1? 2016
 
 
https://eng.uber.com/schemaless-part-one/
 
 
Designing Schemaless of the Uber Engineering data warehouse using MySQL
 
 
Designing Schemaless data warehouse Uber Engineering using MySQL. This is the first part of the three part series of articles on the Schemaless data warehouse.
 
 
In Project Mezzanine we have described , as we moved the data about Uber trips from one copy of Postgres to Schemaless - our high-performance and reliable data store. This article describes its architecture, its role in the Uber infrastructure and the ...[/h]
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Compare Tarantool with Redis and Memcached

Compare Tarantool with Redis and Memcached
 
Choose between Tarantool and Redis or between Tarantool and Memcached ? Let's look at the main differences, so that it's easier for you to decide. [1] . In Tarantool operations on data groups reached an even higher level of complexity, and in terms of reliability of storage (persistence) and indexing Tarantool exceeds Redis , not to mention the speed of work and support for users [2] . Given the development of storage facilities, as well as ...
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