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In this SQL tutorial, you'll learn how to insert records into a table by using the SQL INSERT INTO statement. Learn how to use the SQL INSERT statement.
We'll discuss the syntax of INSERT, and then we'll use an example to show all the different ways you can use INSERT. We'll also combine it with other helpful clauses to perform more complex operations.
INSERT
statementYou use the SQL INSERT INTO statement to insert new records in a table. The syntax of the SQL INSERT INTO statement is:
INSERT INTO table_name (column1, column2, column3, ...)
VALUES (value1, value2, value3, ...);
INSERT
Let's say we have a table called Persons
with the following columns:
PersonID
LastName
FirstName
Address
City
Let's first create the table:
I am using this query to create the table:
CREATE TABLE Persons (
PersonID int,
LastName varchar(255),
FirstName varchar(255),
Address varchar(255),
City varchar(255)
);
On running the query will create the table.
We can insert a new record into the Persons
table by using the following SQL statement:
INSERT INTO Persons (PersonID, LastName, FirstName, Address, City)
VALUES (1, 'Wilson', 'John', '123 Main St.', 'Anytown');
Here is the table with the data inserted:
INSERT
StatementWe can insert multiple records into a table by using a single SQL statement. The following SQL statement inserts three new records into the Persons
table:
INSERT INTO Persons (PersonID, LastName, FirstName, Address, City)
VALUES (1, 'Wilson', 'John', '123 Main St.', 'Anytown'),
(2, 'Smith', 'Mary', '456 Maple St.', 'Anytown'),
(3, 'Jones', 'David', '789 Elm St.', 'Anytown'),
(4, 'John', 'David', '789 Elm St.', 'Meru');
When running the query on TablePlus, it will look like this:
Here is the table with the data inserted:
We can insert records into a table from another table using the SQL INSERT INTO SELECT statement.
The following SQL statement inserts all records from the Persons
table into the PersonsBackup
table:
INSERT INTO PersonsBackup
SELECT * FROM Persons;
In order to run this query, we need to create a new table called PersonsBackup
:
CREATE TABLE PersonsBackup (
PersonID int,
LastName varchar(255),
FirstName varchar(255),
Address varchar(255),
City varchar(255),
PRIMARY KEY (PersonID)
);
Now we can run the query to insert the records from the Persons
table into PersonsBackup
table:
INSERT INTO PersonsBackup
SELECT * FROM Persons;
Here is the table with the data inserted:
We can insert records from a SELECT statement into a table by using the SQL INSERT INTO SELECT statement. The following SQL statement inserts all records from the Persons
table into the PersonsBackup
table:
INSERT INTO PersonsBackup
SELECT * FROM Persons;
Here is the table with the data inserted:
We can insert records into a table from a SELECT statement with a WHERE clause by using the SQL INSERT INTO SELECT statement.
The following SQL statement inserts all records from the Persons
table into the PersonsBackup
table where the City
is Anytown
:
Let's first delete the records from the PersonsBackup
table:
DELETE FROM PersonsBackup;
Now that the records have been deleted, we can insert the records from the Persons
table into the PersonsBackup
table where the City
is Anytown
:
INSERT INTO PersonsBackup
SELECT * FROM Persons WHERE City = 'Anytown';
Inserting records from the Persons
table into the PersonsBackup
table where the City
is Anytown
:
Here is the table with the data inserted:
We can insert records into a table from a SELECT statement with a WHERE clause and a LIMIT clause by using the SQL INSERT INTO SELECT statement.
The following SQL statement inserts the first 10 records from the Persons
table into the PersonsBackup
table where the City
is Anytown
:
Let's first create at least 10 records in the Persons
table where the City
is Anytown
:
INSERT INTO Persons(PersonID, LastName, FirstName, Address, City)
VALUES (5, 'Wilson', 'John', '123 Main St.', 'Anytown'),
(6, 'Smith', 'Mary', '456 Maple St.', 'Anytown'),
(7, 'Jones', 'David', '789 Elm St.', 'Anytown'),
(8, 'John', 'David', '789 Elm St.', 'Anytown'),
(9, 'Wilson', 'John', '123 Main St.', 'Anytown'),
(10, 'Smith', 'Mary', '456 Maple St.', 'Anytown'),
(11, 'Jones', 'David', '789 Elm St.', 'Anytown'),
(12, 'John', 'David', '789 Elm St.', 'Anytown'),
(13, 'Wilson', 'John', '123 Main St.', 'Anytown'),
(14, 'Smith', 'Mary', '456 Maple St.', 'Anytown');
The values have been inserted into the Persons
table:
The table now has 14 records:
We can also add records with the city name being anything other than Anytown
:
INSERT INTO Persons(PersonID, LastName, FirstName, Address, City)
VALUES (15, 'Jones', 'David', '789 Elm St.', 'New York'),
(16, 'John', 'David', '789 Elm St.', 'New York'),
(17, 'Wilson', 'John', '123 Main St.', 'New York'),
(18, 'Smith', 'Mary', '456 Maple St.', 'New York');
The values have been inserted into the Persons
table:
The data with different cities has been inserted into the Persons
table:
Now that we have at least 10 records in the Persons
table where the City
is Anytown
, we can insert the first 10 records from the Persons
table into the PersonsBackup
table where the City
is Anytown
:
We will first delete the records from the PersonsBackup
table:
DELETE FROM PersonsBackup;
The PersonsBackup
table is now empty:
We can now insert the first 10 records from the Persons
table into the PersonsBackup
table where the City
is Anytown
:
INSERT INTO PersonsBackup
SELECT * FROM Persons WHERE City = 'Anytown' LIMIT 10;
You use the limit clause to limit the number of records to be inserted into the PersonsBackup
table. In this case, we are inserting the first 10 records from the Persons
table into the PersonsBackup
table where the City
is Anytown
.
You use the where clause to specify the condition that must be met for the records to be inserted into the PersonsBackup
table. In this case, the City
must be Anytown
for the records to be inserted into the PersonsBackup
table.
When we run the above query, the first 10 records from the ePersons
table where the City
is Anytown
will be inserted into the PersonsBackup
table:
Running the above query:
The records have been inserted into the PersonsBackup
table:
We can insert records from a SELECT statement with a WHERE clause and an ORDER BY clause into a table by using the SQL INSERT INTO SELECT statement.
The following SQL statement inserts all records from the Persons
table into the PersonsBackup
table where the City
is Anytown
and orders the records by LastName
.
Let's first delete the records from PersonsBackup
table:
DELETE FROM PersonsBackup;
The PersonsBackup
table is now empty.
Now, we can insert all records from the Persons
table into the PersonsBackup
table where the City
is Anytown
and order the records by LastName
:
INSERT INTO PersonsBackup
SELECT * FROM Persons WHERE City = 'Anytown' ORDER BY LastName;
Here is the Persons
table before the query is run:
Here is the PersonsBackup
table after the records have been inserted:
We can insert records into a table from a SELECT statement with a WHERE clause and an ORDER BY clause and a LIMIT clause by using the SQL INSERT INTO SELECT statement.
The following SQL statement inserts the first 10 records from the Persons
table into the PersonsBackup
table where the City
is Anytown
and orders the records by LastName
.
First, let's delete the records from PersonsBackup
table:
DELETE FROM PersonsBackup;
Run the query above on your database management tool. I am using TablePlus.
After running the delete query, here is the result:
The PersonsBackup
table is now empty.
INSERT INTO PersonsBackup
SELECT * FROM Persons WHERE City = 'Anytown' ORDER BY LastName LIMIT 10;
Running the above query on TablePlus:
Here is the PersonsBackup
table after the records have been inserted:
We can insert records from a SELECT statement with a WHERE clause, an ORDER BY clause, a LIMIT clause, and an OFFSET clause by using the SQL INSERT INTO SELECT statement.
The following SQL statement inserts the records from the Persons
table into the PersonsBackup
table where the City
is Anytown
. It orders the records by LastName
, limits the records to 10, and skips the first 5 records.
We'll start with the OFFSET
clause. The OFFSET
clause is used to skip the first n
records. In this case, we are skipping the first 5 records.
First, let's delete the records from the PersonsBackup
table:
DELETE FROM PersonsBackup;
Run the query above on your database management tool.
After running the delete query, here is the result.
INSERT INTO PersonsBackup
SELECT * FROM Persons WHERE City = 'Anytown' ORDER BY LastName LIMIT 10 OFFSET 5;
Since we have skipped the first 5 records, the first 5 records in the Persons
table are not inserted into the PersonsBackup
table. This means only 8 records out of 13 records are inserted into the PersonsBackup
table, where City is equal to Anytown.
In this tutorial, you have learned how to insert records into a table by using the SQL INSERT INTO statement.
You have also learned how to insert records into a table with a SELECT statement by using the SQL INSERT INTO SELECT statement.
Original article source at https://www.freecodecamp.org
#sql #database
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SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:
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2. Every database seller needs an approach to separate its item from others.
Right now, contrasts are noted where fitting.
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If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
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The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.
This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.
As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).
This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.
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Currently, the demand for the skill of SQL is on the rise. Most of the jobs describe their skill requirements, and while doing that, they mention the knowledge in SQL specifically. As the name suggests, ‘Data Science’ is data-driven. Thus, SQL will be an integral part of any data science job. It is also because of the advantage that it offers among the other alternatives. This article tries to elaborate on why SQL and querying are essential for data science and related roles.
If you want to learn SQL for data science, then you can start your journey here!
Structured Query Language, acronymized to SQL, is a computer programming language aimed and designed to manipulate data warehoused in RDBMSs, i.e., Relational Database Management Systems. Different functions such as insertion, deletion, updating, modification of data can be done using SQL. Since most of the structured data is stored in RDBMSs, working with data science will necessarily involve RDBMS and, hence, SQL.
With the advent of big data, data warehousing using relational database management systems has gained more importance, and it is strictly necessary to use them. Moreover, traditionally along with the programming languages Python and R, SQL is used. For instance, a data scientist can write an SQL query to extract data from a database, on which further analyses can be made using Python or R.
If you want to become a data scientist, then you can start your journey here!
Data Science is simply the analysis and study of data to extract meaningful insights. SQL comes into the picture in two of the most critical steps of a data science cycle — Data Extraction, the pre-processing step, as mentioned in the introduction, and Machine Learning. Most of the database platforms are designed using SQL, as it has become a standard for database systems. Also, it is easy to communicate with databases with complex instructions and manipulate data.
Modern systems such as Hadoop, Spark use SQL to maintain relational database systems and to process structured data. Identification of suitable data sources and pre-processing are the key steps in any data analysis work. Since the data is stored in relational databases, querying to extract the data without copying the entire database is necessary as it saves time and is efficient. Hence, a data scientist needs to have comprehensive knowledge in querying language, SQL.
SQL is a comprehensive language with several functions, statements, and operators that pave the way to seamless data extraction. SQL has multiple reasons to assert its importance and relevance in data science. First of all, even though SQL has a wide range of tools available, learning them is not an arduous task, as the commands and queries in SQL are comparable to simple English. For example, consider the SQL query ‘select name, nationality from employee’, which can be comprehended by any person of its function with its simplicity of language. Thus, a data science novice can quickly learn SQL, unlike the other programming languages that require more conceptual understanding.
#data-analysis #data #data-science #sql #data-visualization #sql
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The pandemic has brought a period of transformation across businesses globally, pushing data and analytics to the forefront of decision making. Starting from enabling advanced data-driven operations to creating intelligent workflows, enterprise leaders have been looking to transform every part of their organisation.
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