Last Execution of Stored Procedure in SQL Server

Introduction

In an ERP project or any other big applications, there may be many Stored Procedures used. But we are not sure that all the stored procedures are required or not or valid ones. While the requirement(s) has changed, we may ended with another new stored procedure or based on the performance we may have created a new stored procedures and those old or unused stored procedures may not be deleted.

In this article, let’s have a look at, the list of stored procedures with last execution time. This will help us to know whether the stored procedure is required or not in the Database and also helps in clean up process.

Last Execution of Stored Procedure

Let’s run a simple T-SQL to get the list of stored procedures with number of times executed and when it was last executed.

SELECT  
          SCHEMA_NAME(sysobject.schema_id) AS SchemaName,
          OBJECT_NAME(PS.object_id) AS ProcedureName, 
          execution_count AS NoOfTimesExecuted,
          PS.last_execution_time AS LastExecutedOn
    FROM   
         sys.dm_exec_procedure_stats PS
         INNER JOIN sys.objects sysobject ON sysobject.object_id =   
         PS.object_id 
    WHERE  
         sysobject.type = 'P'
    ORDER BY
         PS.last_execution_time DESC  

When the above T-SQL is ran, it will select or display the data from the SQL server Cache.

Note – If the Cache is Cleared or SQL services restarts, the data will reset.

Fig 1. List of Stored Procedures with Last Executed Time

#sql server #last execution of stored procedure #sp last executed #sql #sql query #t-sql

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Introduction to Structured Query Language SQL pdf

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:

1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.

2. Every database seller needs an approach to separate its item from others.

Right now, contrasts are noted where fitting.

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PySQL Tutorial: A Database Framework for Python

PySQL 

PySQL is database framework for Python (v3.x) Language, Which is based on Python module mysql.connector, this module can help you to make your code more short and more easier. Before using this framework you must have knowledge about list, tuple, set, dictionary because all codes are designed using it. It's totally free and open source.

Tutorial Video in English (Watch Now)

Installation

Before we said that this framework is based on mysql.connector so you have to install mysql.connector first on your system. Then you can import pysql and enjoy coding!

python -m pip install mysql-connector-python

After Install mysql.connector successfully create Python file download/install pysql on the same dir where you want to create program. You can clone is using git or npm command, and you can also downlaod manually from repository site.

PyPi Command

Go to https://pypi.org/project/pysql-framework/ or use command

pip install pysql-framework

Git Command

git clone https://github.com/rohit-chouhan/pysql

Npm Command

Go to https://www.npmjs.com/package/pysql or use command

$ npm i pysql

Snippet Extention for VS Code

Install From Here https://marketplace.visualstudio.com/items?itemName=rohit-chouhan.pysql

Table of contents

• Connecting a Server
• Create a Database in Server
• Drop Database
• Connecting a Database
• Creating Table in Database
• Drop Table in Database
• Selecting data from Table
• Add New Column to Table
• Modify Column to Table
• Drop Column from Table
• Manual Execute Query
• Inserting data
• Updating data
• Deleting data

Connecting a Server

---

To connect a database with localhost server or phpmyadmin, use connect method to establish your python with database server.

import pysql

db = pysql.connect(
    "host",
    "username",
    "password"
 )

Create a Database in Server

---

Creating database in server, to use this method

import pysql

db = pysql.connect(
    "host",
    "username",
    "password"
 )
 pysql.createDb(db,"demo")
 #execute: CREATE DATABASE demo

Drop Database

---

To drop database use this method .

Syntex Code -

pysql.dropDb([connect_obj,"table_name"])

Example Code -

pysql.dropDb([db,"demo"])
#execute:DROP DATABASE demo

Connecting a Database

---

To connect a database with localhost server or phpmyadmin, use connect method to establish your python with database server.

import pysql

db = pysql.connect(
    "host",
    "username",
    "password",
    "database"
 )

Creating Table in Database

---

To create table in database use this method to pass column name as key and data type as value.

Syntex Code -

pysql.createTable([db,"table_name_to_create"],{
    "column_name":"data_type", 
    "column_name":"data_type"
})

Example Code -

pysql.createTable([db,"details"],{
    "id":"int(11) primary", 
     "name":"text", 
    "email":"varchar(50)",
    "address":"varchar(500)"
})

2nd Example Code -

Use can use any Constraint with Data Value

pysql.createTable([db,"details"],{
    "id":"int NOT NULL PRIMARY KEY", 
     "name":"varchar(20) NOT NULL", 
    "email":"varchar(50)",
    "address":"varchar(500)"
})

Drop Table in Database

---

To drop table in database use this method .

Syntex Code -

pysql.dropTable([connect_obj,"table_name"])

Example Code -

pysql.dropTable([db,"users"])
#execute:DROP TABLE users

Selecting data from Table

---

For Select data from table, you have to mention the connector object with table name. pass column names in set.

Syntex For All Data (*)-

records = pysql.selectAll([db,"table_name"])
for x in records:
  print(x)

Example - -

records = pysql.selectAll([db,"details"])
for x in records:
  print(x)
#execute: SELECT * FROM details

Syntex For Specific Column-

records = pysql.select([db,"table_name"],{"column","column"})
for x in records:
  print(x)

Example - -

records = pysql.select([db,"details"],{"name","email"})
for x in records:
  print(x)
#execute: SELECT name, email FROM details

Syntex Where and Where Not-

#For Where Column=Data
records = pysql.selectWhere([db,"table_name"],{"column","column"},("column","data"))

#For Where Not Column=Data (use ! with column)
records = pysql.selectWhere([db,"table_name"],{"column","column"},("column!","data"))
for x in records:
  print(x)

Example - -

records = pysql.selectWhere([db,"details"],{"name","email"},("county","india"))
for x in records:
  print(x)
#execute: SELECT name, email FROM details WHERE country='india'

Add New Column to Table

---

To add column in table, use this method to pass column name as key and data type as value. Note: you can only add one column only one call

Syntex Code -

pysql.addColumn([db,"table_name"],{
    "column_name":"data_type"
})

Example Code -

pysql.addColumn([db,"details"],{
    "email":"varchar(50)"
})
#execute: ALTER TABLE details ADD email varchar(50);

Modify Column to Table

---

To modify data type of column table, use this method to pass column name as key and data type as value.

Syntex Code -

pysql.modifyColumn([db,"table_name"],{
    "column_name":"new_data_type"
})

Example Code -

pysql.modifyColumn([db,"details"],{
    "email":"text"
})
#execute: ALTER TABLE details MODIFY COLUMN email text;

Drop Column from Table

---

Note: you can only add one column only one call

Syntex Code -

pysql.dropColumn([db,"table_name"],"column_name")

Example Code -

pysql.dropColumn([db,"details"],"name")
#execute: ALTER TABLE details DROP COLUMN name

Manual Execute Query

---

To execute manual SQL Query to use this method.

Syntex Code -

pysql.query(connector_object,your_query)

Example Code -

pysql.query(db,"INSERT INTO users (name) VALUES ('Rohit')")

Inserting data

---

For Inserting data in database, you have to mention the connector object with table name, and data as sets.

Syntex -

data =     {
    "db_column":"Data for Insert",
    "db_column":"Data for Insert"
}
pysql.insert([db,"table_name"],data)

Example Code -

data =     {
    "name":"Komal Sharma",
    "contry":"India"
}
pysql.insert([db,"users"],data)

Updating data

---

For Update data in database, you have to mention the connector object with table name, and data as tuple.

Syntex For Updating All Data-

data = ("column","data to update")
pysql.updateAll([db,"users"],data)

Example - -

data = ("name","Rohit")
pysql.updateAll([db,"users"],data)
#execute: UPDATE users SET name='Rohit'

Syntex For Updating Data (Where and Where Not)-

data = ("column","data to update")
#For Where Column=Data
where = ("column","data")

#For Where Not Column=Data (use ! with column)
where = ("column!","data")
pysql.update([db,"users"],data,where)

Example -

data = ("name","Rohit")
where = ("id",1)
pysql.update([db,"users"],data,where)
#execute: UPDATE users SET name='Rohit' WHERE id=1

Deleting data

---

For Delete data in database, you have to mention the connector object with table name.

Syntex For Delete All Data-

pysql.deleteAll([db,"table_name"])

Example - -

pysql.deleteAll([db,"users"])
#execute: DELETE FROM users

Syntex For Deleting Data (Where and Where Not)-

where = ("column","data")

pysql.delete([db,"table_name"],where)

Example -

#For Where Column=Data
where = ("id",1)

#For Where Not Column=Data (use ! with column)
where = ("id!",1)
pysql.delete([db,"users"],where)
#execute: DELETE FROM users WHERE id=1

--- Finish ---

Change Logs

[19/06/2021]
 - ConnectSever() removed and merged to Connect()
 - deleteAll() [Fixed]
 - dropTable() [Added]
 - dropDb() [Added]
 
[20/06/2021]
 - Where Not Docs [Added]

The module is designed by Rohit Chouhan, contact us for any bug report, feature or business inquiry.

Author: rohit-chouhan
Source Code: https://github.com/rohit-chouhan/pysql
License: Apache-2.0 License

#python 

Last Execution of Stored Procedure in SQL Server

Introduction

In an ERP project or any other big applications, there may be many Stored Procedures used. But we are not sure that all the stored procedures are required or not or valid ones. While the requirement(s) has changed, we may ended with another new stored procedure or based on the performance we may have created a new stored procedures and those old or unused stored procedures may not be deleted.

In this article, let’s have a look at, the list of stored procedures with last execution time. This will help us to know whether the stored procedure is required or not in the Database and also helps in clean up process.

Last Execution of Stored Procedure

Let’s run a simple T-SQL to get the list of stored procedures with number of times executed and when it was last executed.

SELECT  
          SCHEMA_NAME(sysobject.schema_id) AS SchemaName,
          OBJECT_NAME(PS.object_id) AS ProcedureName, 
          execution_count AS NoOfTimesExecuted,
          PS.last_execution_time AS LastExecutedOn
    FROM   
         sys.dm_exec_procedure_stats PS
         INNER JOIN sys.objects sysobject ON sysobject.object_id =   
         PS.object_id 
    WHERE  
         sysobject.type = 'P'
    ORDER BY
         PS.last_execution_time DESC  

When the above T-SQL is ran, it will select or display the data from the SQL server Cache.

Note – If the Cache is Cleared or SQL services restarts, the data will reset.

Fig 1. List of Stored Procedures with Last Executed Time

#sql server #last execution of stored procedure #sp last executed #sql #sql query #t-sql

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

• revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
• microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
• Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

SCHEMAS in SQL Server -MS SQL Server – Zero to Hero Query Master

Introduction

This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,

• MS SQL Server – Zero to Hero Query Master – Part 1
• MS SQL Server – Zero to Hero Query Master – Part 2

A glimpse of previous articles

Part 1

In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.

Part 2

• We learned to create a database and maintain it using SQL statements.
• Best practice methods were also mentioned.

#sql server #benefits of schemas #create schema in sql #database schemas #how to create schema in sql server #schemas #schemas in sql server #sql server schemas #what is schema in sql server