Complete Responsive Login Form in HTML and CSS Tutorial – Log In Form Design
A clean, simple, and easy-to-use login page design HTML CSS tutorial. login form in HTML and CSS step-by-step coding tutorial for learning.
We showed everything with HTML and CSS. So that by watching this video tutorial you can learn HTML and CSS. This HTML and CSS login page.
With the move to responsive websites, a lot of blogs are shifting away from using flash-based login forms. HTML5, CSS3, and JavaScript are changing the way that this experience is delivered. how to build a login form using HTML5, CSS3, and JavaScript. If you are curious about this style of website design, this should give you a good idea of what it would be like.
Complete Responsive Login Form in HTML and CSS Tutorial – Log In Form Design
Backend Engineering: Log-Structured-Tree
Today I will talk about a data structure used to create a database. Usually we are introduced to database with transactional database of Sql type, like MySQL, PostGreSQL. Data is stored using B+ Tree in these databases. In this article I will discuss another popular data structure for building databases called Log-Structured-Tree or LSM Tree for short.
As mentioned earlier, this is not a data structure to be used in programming contexts. But the LSM Tree is an example of why software engineers need to know about data structures, algorithms, and hardware.
Those working on backend engineering often have to work with NoSQL databases like Hive, BigTable, Rocks-DB. Most of these databases are created using LSM Tree. Knowing about LSM Tree will help in optimizing database performance or deciding which database to use will get better results.
I would hope that those reading this have at least a little experience working with databases, know about database indexes or the difference between SQL/NoSql.
In bold, any database performs two types of operations, data reading (Read) or data writing (Write). Data from some databases can be read very quickly but the writing speed is a bit slow, while some databases can be inserted quickly but the data reading performance is a bit poor.
Which type of database you use depends on your system requirements. If you want to make an app to publish SSC exam results, then you must focus more on reading data, but if you want to save where and when a user clicks on an e-commerce site in a database for later analysis, then on Write should be given importance.
LSM Tree mainly focuses on write operations, while B+ tree based database works better when there are more read operations. There are also more differences, more on that later.
Sequential read-write
To know about LSM Tree we need to go a little low-level. Any storage device (eg hard disk) is divided into small blocks to save data. Some bytes are saved in each block. Now there are some advantages if your data is saved in blocks as well.
Sequential access means accessing data stored side by side one by one. And in the case of random access, we have to jump from one block to another distant block.
Hard disk (HDD – Hard disk drive) was used everywhere as a storage device some time ago. On the hard disk, a circular disk rotates and data is read from a specific block by moving a pin back and forth.
As you can see, random access to data on the hard disk will naturally take longer because the location of the pins has to be changed repeatedly. Those who have used computers during Windows 98, must remember disk defragment software. It’s job was to sort the random data together.
Solid State Drives (SSDs) are currently used in data centers, SSDs are also popular in most newer models of laptops. SSDs do not have disks, instead data is stored in semiconductors. SSD’s read-write performance is much better than traditional hard disk. In this case, the difference between random access and sequential access is reduced, but sequential access gives slightly better performance. This difference is very important when we write several terabytes of data.
Talking about the data structure, the reason for pulling these is that LSM Tree always saves data sequentially, thereby increasing the write performance many times. Sequential writes are not always possible due to the structure of the B+ tree.
log structure
Logs are probably the simplest data structure in the world. Logging generally refers to writing down what events are happening one by one. This can be done using text files or binary files. When you are browsing a website, where and when you click, when you view which pages are written in a log file. Later, this log file can be analyzed with a machine learning algorithm to find out your likes and dislikes, e-commerce or social network sites are constantly doing this.
Database logs are needed to recover data. When you issue a biwind update command to a database, that command is written to a log file, and then the database is updated. By doing this, even if the database crashes before the update, the database can be recovered from the log. Such log is called Write Ahead Log (WAL). After reading this article, you can google WAL and know more about it.
Complete Responsive Login Form in HTML and CSS Tutorial – Log In Form Design
The important feature of log file is that only one data is written here, it is an Append Only data structure. Normally no changes are made to any data written to this file. That’s why we can take advantage of sequential writes while saving log files. But when data is being written to B+ tree, random access has to be done.
By using LSM Tree instead of B+ Tree we can do sequential writes to the original database as well. We will see that now.
Sorted String Table (SSTable)
Let’s say we are storing the database data in a log file instead of a B+ tree. If you put it in one file, it will be too big, so you have to divide it into many small files. Our data is just some key-value pairs.
Here I am using log in two places. First we write our data in WAL so that data can be recovered in case of any problem. Then saving in log form in the main database. Every time new data comes in we will try to write to the latest file in the database. If the file is too big, I will create a new file.
Once the data is written it cannot be changed, if the data needs to be updated then a new entry must be made. Even if the data is to be deleted, a new key must be inserted and marked with a special flag, it is called Tombstone data.
(That’s why a lot of duplicate data will be created in the database, the solution to that problem will be discussed later)
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