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Introduction to PostgreSQL REGEXP_REPLACE

The regular expression is a sequence of characters, the short name for the list of strings. If any string matches with any of the strings, which is part of a list of the strings defined by the regular expression. PostgreSQL supports the regular expression, and the function provided by PostgreSQL is used to replace substrings with a new substring that matches a POSIX regular expression. The PostgreSQL REGEXP_REPLACE() function uses a POSIX regular expression pattern.

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Syntax:

REGEXP_REPLACE(input_string, regex_pattern, replace_string,[, flags])

Explanation:

input_string: This defines the input string in which replacement should be taken place for a specified pattern, a POSIX regular expression.

regex_pattern: This defines the POSIX regular expression to match the string.

flags: This flag is used to control the behavior of the REGEXP_REPLACE() function, This can have the value of one or more characters.

Replace_string: This string defines a string that replaces the substring, which matches the POSIX regular expression pattern.

Examples of PostgreSQL REGEXP_REPLACE

Here are the following examples of implementing the PostgreSQL REGEXP_REPLACE function

Consider the following name format like the first name and then last name:

‘Jacob David’

Suppose we want to re-arrange the last name and the first name for purposes like the last name and then the first name. So, we can use the PostgreSQL REGEXP_REPLACE() function to do this as follows:

SELECT REGEXP_REPLACE('Jacob David', '(.*) (.*)', '2, 1');

Illustrate the result of the above statement by using the following snapshot.

Example #2

Example, to remove the string, consider we have a string in the following as follows:

"xyz54321ABC"

Now, we will remove all alphabets characters from the above string by using the following statement:

SELECT REGEXP_REPLACE('xyz54321ABC', '[[:alpha:]]', '', 'g');

Illustrate the result of the above statement by using the following snapshot.

Now, we will remove all digits from the above string by using the following statement:

SELECT REGEXP_REPLACE('xyz54321ABC', '[[:digit:]]', '', 'g');

Illustrate the result of the above statement by using the following snapshot.

In the above examples, we have used the following regular expressions.

'[[:alpha:]]' '[[:digit:]]'

Also, we have used the replacement string as ‘’ and the flag ‘g’ we have used to instruct the PostgreSQL REGEXP_REPLACE function to replace all of the occurrences of the matched string and not just the first occurrence.

Example #3

Remove multiple occurrences of the spaces. Consider the following example, which removes more than one space that occurred in a string. Consider the following statement to do the same.

SELECT REGEXP_REPLACE('PostgreSQL is awesome database', '( ){2,}', ' ', 'g');

Illustrate the result of the above statement by using the following snapshot.

Example #4

We will create a table named ‘student’ by using the CREATE TABLE statement as follows:

create table student ( stud_id serial PRIMARY KEY, stud_fname VARCHAR(80) NOT NULL, stud_lname VARCHAR(80) NOT NULL );

Now, we will insert some data into the student table by using the INSERT INTO statement as follows

INSERT INTO student(stud_fname,stud_lname) VALUES ('Smith','Johnson'), ('Williams','Jones'), ('Brown','Davis');

Illustrate the above INSERT statement’s result using the following SQL statement and snapshot.

select * from student;

Consider the following SQL statement where we are checking whether the stud_lname is having ‘Jo’ substring, and if it exists, then we replace it with ‘K.’

SELECT REGEXP_REPLACE(stud_lname , 'Jo', 'K') AS "New Name" FROM student;

Also, consider the other example,

Consider the following SQL statement where we are checking whether the stud_lname is having ‘s’ substring, and if it exists, then we replace it with ‘K’

SELECT REGEXP_REPLACE(stud_lname , 's', 'K') AS "New Name" FROM student;

Illustrate the result of the above SQL statement by using the following snapshot.

Advantages of using PostgreSQL REGEXP_REPLACE () function

1. The PostgreSQL REGEXP_REPLACE () function supports various flags,

Consider examples like:

flag ‘i’ : match case-insensitively

flag ‘g’: search globally for each occurrence.

2. The PostgreSQL REGEXP_REPLACE() replaces all occurrences of the substring with the new string.

3. We can use The PostgreSQL REGEXP_REPLACE() function, the substring in variable length or dynamic strings.

Conclusion

From the above article, we hope you understand how to use the PostgreSQL REGEXP_REPLACE() function and how the PostgreSQL REGEXP_REPLACE() function works. Also, we have added several examples of the PostgreSQL REGEXP_REPLACE() function to understand it in detail.

Learn The Implementation Of Db2 Cast With Examples

Introduction to DB2 CAST

DB2 CAST is a function available in DB2 that is used for explicit conversion of the data type of a particular value to another datatype. DB2 comes with the default facility of trying to convert the datatypes of the values if they are not mentioned properly to an expected data type value in all the functions and the instructions that are issued and where there is a necessity of doing so. This is called implicit casting or conversion of a datatype. In this article, we will study how we can convert the value of one data type to another with the help of the CAST() function available in DB2, the syntax of the CAST() function, and the implementation with the help of certain examples.

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Syntax

CAST(any expression or value AS the required datatype)

In the above expression, the expression or value can be any field value of a particular table column or a constant value, or even a variable that holds a certain value. The required data type is the data type that you want the value mentioned as the expression to be converted to. We can specify any data type, we want the data to convert to such as int, string, etc.

Implicit casting in DB2 Examples

Consider the following example where we are trying to add 6 integer value with ‘16’ string value using the plus(+) operator and retrieve the result –

6 + ’16’ as result ;

The execution of the above query statement gives the following output with the resultant value being an integer which is 22. Over here, DB2 firstly converted the string ‘16’ to an integer value and then went for doing the addition.

Let us consider one more example where we will be using the concatenation operator which is a string operator and works only with string. When we use the same values specified in the above example 6 and ‘16’ which are an integer and a string, using the following query statement –

The execution of the above query statement gives the following output with the resultant value being a string which is 616. Over here, DB2 firstly converted the integer 6 to string value and then goes for doing the concatenation.

Now, let us see, how we can cast the values explicitly using the CAST() function. If the values cannot be cast by the DB2 due to incompatible type of values, it throws an error saying as shown in the below image –

Now, let us try to convert a decimal value to an integer value using the DB2 CAST() function which will do explicit datatype conversion for us. Consider the following query statement where we are trying to convert a decimal number 14.562 to and integer value to get a rounded whole number. We can do this by using the following query statement with the CAST() function in it –

The output of the above query statement is a rounded integer value of 14.562 which is 14 as shown below –

Now, consider a decimal number 16.5454 which we want to cast to a decimal number itself but a lower scale value to it. We can even do this by using the CAST() function and our query statement, in this case, will look as follows –

CAST ( 16.5454 DEC (4,2)) AS result;

The output of the above query statement’s execution is as shown below with the number rounded and cast to a decimal value of two places after a decimal point has a different scale than the original one –

Let us try to convert a value of the TIMESTAMP datatype to the TIME datatype, in order to get only the time value in the output. We will convert the current timestamp value to time using the cast function in the following query statement to retrieve the current time value of the system –

CAST (CURRENT TIMESTAMP AS TIME) as result;

The execution of the above query statement gives the following result where we get the value of the current time of the system from the current TIMESTAMP value which is as shown below –

We can even convert the current timestamp value to the date datatype in order to retrieve today’s date of my system and using the following query statement and the CAST() function –

CAST (CURRENT TIMESTAMP AS DATE) as result;

The output of the execution of the above query statement is as shown below with the date value in it which is the current system date.

Let us try one last example where we will cast the value of string data type to a DATE datatype explicitly by using the CAST() function in DB2 RDBMS. Let us consider a random date value say ‘2030-01-27’. We will try to convert this string to DATE datatype by using the following query statement –

CAST(‘2030-01-27’ AS DATE) result;

The output of the execution of the above query statement in DB2 DBMS gives the following resultant value with the date specified being cast to a DATE data type as shown below –

Conclusion

IN DB2 RDBMS, the datatypes are internally converted into required datatypes while using the functions and manipulations and while doing operations. However, if we want to explicitly convert a particular value to a required datatype then we can make use of the CAST() function to convert the value to a different datatype explicitly in DB2 RDBMS. We can convert the data type f the values to any in-built and user-defined datatype using the CAST() function.

Learn The Examples And Advantages

Introduction to PostgreSQL STRING_AGG()

PostgreSQL supports various kinds of aggregate functions, The STRING_AGG() function is one of the aggregate functions which is used to concatenate the list of strings, and it will add a place to a delimiter symbol or a separator between all of the strings. The separator or a delimiter symbol will not be included at the end of the output string. The PostgreSQL STRING_AGG() function is supported by PostgreSQL 9.0 version, which performs the aggregate option related to the string. We can use various separators or delimiter symbols to concatenate the strings.

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Syntax

Explanation:

The STRING_AGG() function takes input ORDER BY clause is an optional and other two arguments as follows:

expression: This is a character string that is any valid expression.

separator/delimiter: This defines the separator/delimiter used for string concatenation.

The ORDER BY clause is optional and defines the order of concatenated string results.

The ORDER BY has the syntax as follows:

How does PostgreSQL STRING_AGG() function works?

The input expression needed should be a character string data type. We can also use other data types but only need to ensure that we have explicitly cast other data types to the character string data type.

The PostgreSQL STRING_AGG() returns us the result in string type.

The STRING_AGG() is generally used with the GROUP BY clause like we use other PostgreSQL aggregate functions such as MIN(), MAX(), AVG(), SUM(), COUNT(), etc.

Examples to Implement PostgreSQL STRING_AGG() function

We will create a table named ‘student’ and ‘course’ by using the CREATE TABLE statement as follows:

STUDENT TABLE:

create table student ( stud_id serial PRIMARY KEY, stud_name VARCHAR(80) NOT NULL, stud_grade CHAR(1) NOT NULL, stud_country VARCHAR(80) NOT NULL, course_id int NOT NULL );

COURSE TABLE:

create table course ( course_id serial PRIMARY KEY, course_name VARCHAR(80) NOT NULL );

Now, we will insert some data into the ‘course’ table by using the INSERT INTO statement as follows:

INSERT INTO course(course_name) VALUES ('Computer'), ('Mechanical'), ('Civil'), ('Electrical');

Illustrate the above INSERT statement’s result using the following SQL statement and snapshot.

select * from course;

INSERT INTO student(stud_name,stud_grade,stud_country,course_id) VALUES ('Smith','A','USA',1), ('Johnson','B','USA',2), ('Williams','C','USA',3), ('Jones','C','Canada',1), ('Brown','B','Canada',2), ('Davis','A','Canada',3), ('Aarnav','A','India',1), ('Aarush','B','India',2), ('Aayush','C','India',3), ('Abdul','C','UAE',1), ('Ahmed','A','UAE',3), ('Ying', 'A','China',1), ('Yue','B','China',2), ('Feng', 'C','China',3), ('Mian','C','South Korea',1), ('Fei','B','South Korea',2), ('Hong','A','South Korea',3);

Illustrate the above INSERT statement’s result using the following SQL statement and snapshot.

select * from student;

SELECT c.course_name AS "course name", s.stud_name AS "student name" FROM course c RIGHT JOIN student s ON c.course_id = s.course_id ORDER BY 1;

Illustrate the result of the above statement by using the following snapshot.

We can concatenate the student names by using the STRING_AGG() function by modifying the above SQL statement as follows:

SELECT crs.course_name AS "course name", string_agg(stud.stud_name, ', ') AS "student list" FROM course crs JOIN student stud ON crs.course_id = stud.course_id GROUP BY 1 ORDER BY 1;

Illustrate the result of the above statement by using the following snapshot.

SELECT stud_grade, STRING_AGG(stud_name,', ') AS StudentsPerGrade FROM student GROUP BY stud_grade ORDER BY 1 ;

Illustrate the result of the above statement by using the following snapshot.

In the above example, the resulting snapshot shows us the students concatenated by a comma separator with a similar grade obtained.

SELECT STRING_AGG(stud_name, ', ') AS "student_names", stud_country FROM student GROUP BY stud_country;

Illustrate the result of the above statement by using the following snapshot.

In the above example, we observe that the code groups and concatenates all students from the same country, utilizing a comma separator.

Advantages

We can control the order of the result by using the ORDER BY clause.

The PostgreSQL STRING_AGG() function returns the result in string format.

We can use the STRING_AGG() function to concatenate all strings and add a delimiter symbol or separator between them.

The PostgreSQL STRING_AGG() supports various types of delimiter symbols or separators and does not include delimiter symbols or separators at the end of the string.

Conclusion

From the above article, we hope you understand how to use the PostgreSQL STRING_AGG() function and how the PostgreSQL STRING_AGG() function works. Also, we have added several examples of the PostgreSQL STRING_AGG() function to understand it in detail.

Top Points For Successful Erp Implementation

ERP systems are trusted by businesses from all industries. They streamline business processes, increase productivity, reduce wastage, encourage collaboration and increase profits. Advanced ERP solutions provide actionable insights that allow decision-makers to make better decisions. Although ERP has many benefits, implementation can be difficult as it involves a lot of time and money. Implementation is the key to ERP’s success. ERP implementations that are successful will ultimately improve the productivity and efficiency of operations. If ERP isn’t implemented correctly, it can cause a loss of time and money. We offer “Tips for Successful ERP Implementation” in this article.

Understanding Your Business Requirements

It is recommended to first identify the problem areas in your business if you don’t use any ERP or accounting software. You must monitor and control the movement of goods across different channels if your business involves a supply chain. If your accounting software is outdated, you should consider upgrading to a more sophisticated system that will not only increase organizational efficiency but also eliminate data silos.

How to Choose the Best ERP Solution

There are so many options on the market that it is difficult to find the right option for your business. Oracle NetSuite is one of the most widely used options. NetSuite, a cloud-based and true SaaS Business Manager Suite, automates both front- and back-office processes. This allows small and large businesses to quickly respond to market opportunities and make informed decisions. NetSuite offers core capabilities such as financial management, revenue management, fixed assets management, order management, and billing. It also provides real-time visibility of key performance indicators. Available as Software-as-a-Service (SaaS), NetSuite doesn’t require hardware, no large upfront license fee, no maintenance fees associated with hardware or software, and no complex setups. SaaS deployment allows even small businesses to benefit from digital transformation.

Right Implementation Team

Be Precise and Realistic

Manage Change, Avoid Chaos

The installation of ERP can transform many processes and the way employees work. The success of the implementation depends on the quality of your change management planning. Proper planning and execution tactics will prevent confusion and buildup of resistance to impending changes. It would be great to educate your employees about the ERP solution’s benefits.

Inspiring Content Personalization Examples For B2B

Today’s consumers don’t just enjoy content personalization – they expect it.

In this article, we’ll look at why personalization matters, and how to get started implementing personalization across your customer journey.

Why Personalize?

Personalization is all about cutting down the noise and delivering exactly what your customer or client needs to hear.

It’s a way to make a deeper and more meaningful connection with the people you’re trying to reach.

From a business perspective, personalization has a huge return on investment (ROI).

Epsilon research found that when companies use personalization in their content, 80% of customers are more likely to make a purchase.

And according to Google research, a highly personalized shopping experience makes customers 40% more likely to spend more than they had originally planned.

If you want to create high-performing content that delights and engages your customers, personalization is key.

Metadata Is The Key To Personalization

The backbone of any personalization strategy is data.

Metadata is simply information about your data. Why is this important?

Well, to personalize content, you need to connect your customers to the correct content, which means you need data about both customers and content.

Once you collect customer data, you can use this information to create custom content.

Tagging Content

The more information you have about our content, the easier it will be to direct it to the right audience.

One way to do this is by tagging your content with information like audience, persona, funnel stage, and campaign.

You can tag content in many CMS (content management systems) like HubSpot.

Email Personalization

Email is a terrific area to begin incorporating some content personalization.

Let’s look at some examples.

If a tech company sends out a marketing email to its entire email list promoting a sale, that’s pretty good.

But what would be better is sending out a promotional email to different groups based on their persona. This way you can personalize the content based on interest.

We sent this email to prospective customers who may be interested in this white paper based on their persona.

Website History

With some basic analytics, you can discover which website pages your potential clients are spending the most time on.

And if they submit an email address for a newsletter or download, you can follow along their exact journey on your website.

Using this data you can create personalized emails that specifically target the information they’re interacting with.

Now, this strategy isn’t scalable, and it would take way too much time to track every single prospect.

But for B2B businesses, it’s worth it to analyze your prospect journeys and make note of any potentially large and in-target customers.

A few well-placed emails to an already interested prospect can make a world of difference.

Location

If your business is international, you can create marketing emails that reflect the local seasons and holidays of your customers.

More important than trying to recognize each holiday on the planet is simply to recognize that your customers don’t all live in the same area.

I would suggest that not sending a “Welcome Summer” email to your Australian customers at the beginning of June is actually a form of personalization.

Instead, make sure any references to holidays, sports, and weather are relevant to the location where you’re sending the email.

This is a great way to show that you understand the global nature of your business.

Interest

Instead of offering all of your products or services to customers, help them discover content focused on what they’re already interested in.

This could be as simple as asking which topics they’d like to learn more about on an email sign-up form.

You can also use data about what your customers have already purchased, pages they’ve viewed, and videos they’ve watched to set up an interest-based workflow.

Persona

Personalizing content based on persona is especially important for B2B organizations.

The messaging we use to communicate with C-suite professionals is different than how we present our message to technical writers.

Your different target audiences will have different challenges and pain points.

Hopefully, you’re already keeping this in mind when creating your content and tagging it accordingly.

Once you do this, you can easily pull together content for each persona and create an email sequence that speaks directly to them.

Website Content Personalization Buyers Journey

Do you know where your potential customers are on the buyer’s journey?

Someone who’s just hearing about your product for the first time is going to want different information than someone who’s deep in the middle of researching potential options.

You need to make sure that you’re creating a variety of content that reaches the top of the funnel prospects all the way to the bottom of the funnel.

Once you have this content created, you can share it with the appropriate audience. One way to do this is by suggesting more articles to read that are for a similar place in the funnel.

CTA Customization

Calls to action (CTAs) offer your potential customers a clear way to respond to your content and help move them down the funnel.

You should be testing out different CTAs and noting which ones work best.

You can use customized CTAs to deliver a highly-personalized action step.

This first example is a basic CTA. It’s good, but it’s very general.

This CTA is personalized. We know that Jim is interested specifically in laptops, so we personalize the message for him.

Personalization Tools

Creating customized content can seem overwhelming at first, so it’s best to pick one area and test it until you learn what works well for your organization.

And there are plenty of tools out there to help you enable personalization in your content, such as Keystone, Recombee, and Algolia.

The editorial staff also recommends Piano Analytics + Activation.

Conclusion

Begin by solidifying buyer personas and creating contact lists based on them. From there, you could easily create a segmented email campaign.

Soon you’ll be on your way to cultivating better customer experiences.

And once you begin to see the power of personalization in your content, you’ll never go back.

More resources:

Featured Image: Mix and Match Studio/Shutterstock

Learn The Essential Idea Of The Pytorch Sgd

Introduction to PyTorch SGD

In PyTorch, we can implement the different optimization algorithms. The most common technique we know that and more methods used to optimize the objective for effective implementation of an algorithm that we call SGD is stochastic gradient descent. In other words, we can say that it is a class of optimization algorithms. It very well may be viewed as a stochastic guess of angle plunge enhancement since it replaces the genuine slope (determined from the whole informational collection) by a gauge thereof (determined from an arbitrarily chosen subset of the information). This decreases the computational weight, particularly in high-dimensional streamlining issues, accomplishing quicker emphases in exchange for a lower intermingling rate.

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What is PyTorch SGD?

First, how about we talk about what you mean by upgrading a model. We just need the model to arrive at the condition of greatest precision is given asset requirements like time, processing power, memory, and so on. Streamlining has an expansive extension, and you can likewise change the engineering to improve the model. However, that is something that accompanies instinct created by the experience.

The SGD is only Stochastic Gradient Descent; It is an analyzer that goes under angle plunge, which is a renowned enhancement procedure utilized in AI and profound learning. The SGD enhancer where “stochastic” signifies a framework that is associated or connected up with irregular likelihood. In the SGD analyzer, a couple of tests are being gotten, or we can say a couple of tests are being chosen in an arbitrary way rather than taking up the entire dataset for every cycle. We will utilize torch.optim, which is a bundle, executes various improvement calculations for improving a capacity. The few usually utilized strategies are as of now upheld, and the interface is general enough with the goal that more useful ones can be likewise effortlessly incorporated in the future.

Stochastic Gradient Descent is amazingly fundamental and is only occasionally utilized at this point. One issue is with the overall learning rate identified with the same. Henceforth it doesn’t function admirably when the boundaries are in a few scales since an espresso learning rate will make the preparation slow, while an outsized learning rate may cause motions. Likewise, Stochastic Gradient Descent, for the most part, struggles getting away from the seat focuses. Adagrad, Adadelta, RMSprop, and ADAM, for the most part, handle saddle focus better. SGD with force delivers some speed to the improvement and furthermore helps get away from neighborhood minima better.

Using PyTorch SGD Implementation PyTorch SGD

Now let’s see how we can implement the SGD in PyTorch as follows.

Syntax

Explanation

Using the above syntax, we can implement the SGD optimization algorithm as per our requirement; here, we use different parameters.

specified parameters: Specified parameter means iterable parameters that are used to define the distinct group of parameters.

lrv: lrv is nothing but the learning rate value of the optimized algorithm.

mf: This is an afloat and optional part of this syntax, and mf means momentum factor. The default value of mf is 0.

dm: This is also a float and optional part of the syntax. The default value of dampening is 0.

nm: This is a Boolean and optional part of the syntax, and Nesterov momentum’s default value is false.

PyTorch SGD Examples

Now let’s see different examples of SGD in PyTorch for better understanding as follows.

First, we need to import the library that we require as follows.

import torch

After that, we need to define the different parameters that we want as follows.

btch, dm_i, dm_h, dm_o = 74, 900, 90, 12

Here we define the different parameters as shown in the above code; here, btch means batch size, dm_i means input dimension, dm_o output dimension, and h for hidden.

Now create a random tensor by using the following code as follows.

input_a = torch.randn(btch, dm_i) result_b = torch.randn(btch, dm_o) SGD_model = torch.nn.Sequential( torch.nn.Linear(dm_i, dm_h), torch.nn.ReLU(), torch.nn.Linear(dm_h, dm_o), ) l_fun = torch.nn.MSELoss(reduction='sum')

In the next line, we need to define the learning rate value as per our requirements.

r_l = 0.2

In the next step, we need to initialize the optimizer we want with a forwarding pass.

optm = torch.optim.SGD(SGD_model.parameters(), lr=r_l, momentum=0.9) for values in range(600): p_y = SGD_model(input_a) loss = l_fun(p_y, result_b) if values % 100 == 98: print(values, loss.item())

We illustrated the final output of the above code by using the following screenshot as follows.

Conclusion

We hope from this article you learn more about the PyTorch SGD. From the above article, we have taken in the essential idea of the PyTorch SGD, and we also see the representation and example of PyTorch SGD. Furthermore, from this article, we learned how and when we sequential SGD.