Rajendra Gupta

Rajendra Gupta

Rajendra Gupta

Rajendra has 8+ years of experience in database administration having a passion for database performance optimization, monitoring, and high availability and disaster recovery technologies, learning new things, new features.

While working as a Senior consultant DBA for big customers and having certified with MCSA SQL 2012, he likes to share knowledge on various blogs.
He can be reached at rajendra.gupta16@gmail.com

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Rajendra Gupta
SQL FILETABLE root folder structure

Managing Data in SQL Server FILETABLEs

March 22, 2019 by

SQL Server FILETABLE is a next generation feature of SQL FILESTREAM. We can use it to store unstructured objects into a hierarchal directory structure. SQL Server manages SQL FILETABLE using computed columns and interacts with the OS using extended functions. We can manage SQL FILETABLEs similar to a relational table.

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comparison on transaction log growth between Accelerated Database Recovery feature On and Off.

Accelerated Database Recovery and Long Running Transactions with Transaction Log Growth

March 21, 2019 by

In my previous article in this series Accelerated Database Recovery; Instant Rollback and Database Recovery, we talked about a potential DBA painkiller to resolve long waiting times for database recovery and rollback scenarios using Accelerated Database Recovery. In this article, we will look at one more painful challenge for DBAs, Long Running Transaction with Transaction log growth.

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SQL FILETABLE root folder structure and child folder mapping with SQL Server FILETABLE

SQL Server FILETABLE – the next generation of SQL FILESTREAM

March 11, 2019 by

This SQL Server FILETABLE article is the continuation of the SQL Server FILESTREAM series. The SQL Server FILESTREAM feature is available from SQL Server 2008 on. We can store unstructured objects into FILESTREAM container using this feature. SQL Server 2012 introduced a new feature, SQL Server FILETABLE, built on top of the SQL FILESTREAM feature. In this article, we will explore the SQL FILETABLE feature overview and its comparison with SQL FILESTREAM.

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Importing compressed data into SQL Server: Add an OLE DB destination

Importing Data into SQL Server from Compressed Files

March 5, 2019 by

Introduction

I have seen many organizations receive data from various sources and import into SQL Server. You might receive data in various formats and want to import into SQL Server. We can prepare a ETL (Extract-Transform-Load) process to import data into the SQL Server. In doing so, might receive data in a compressed file, which helps to send data over the network using a ZIP file format because it reduces the file size significantly. If we are receiving a ZIP file to import into SQL Server, we need to unzip it and then only we can import data. We might need to create a ZIP file as well from the existing files.

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SQL FILESTREAM demo backup

Transaction log backups in a SQL FILESTREAM database

March 5, 2019 by

In the continuation of our SQL FILESTREAM article series, we’ll be covering transaction log backups

In SQL Server, we take transaction log backups regularly to have a point-in-time recovery of a database. It is essential to define the backup policy with the combination of full, differential and transaction log backups. A standard configuration of backups for large databases in the production database environment is as follows.

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Execcute and monitor status of SQL Server Python SSIS package

Using Python SQL scripts for Importing Data from Compressed files

March 4, 2019 by

Using Python SQL scripts is a powerful technical combination to help developers and database administrators to do data analytics activities. Python provides many useful modules to perform data computation and processing of data efficiently. We can run Python scripts starting from SQL Server 2017. We can create the ETL solutions to extract data from various sources and insert into SQL Server.

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Selecting the Pie Charts Tree in thhe Power BI application marketplace

Power BI Desktop Pie Chart Tree

February 27, 2019 by

Power BI Desktop amplifies the value of data. We can connect to multiple data sources and visualize the data interactively. One of the best parts of Power BI Desktop is the custom visual feature. It allows developers to create custom visuals and users can then download these visuals from the marketplace and use it as per the data set requirements. We can prepare reports using Power BI Desktop and share the reports using the Power BI service.

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SQL Server FILESTREAM with Change Data Capture

February 22, 2019 by

Sometimes we require tracking data change activity (Insert, update and deletes) in SQL Server tables. SQL Server 2008 introduced Change Data Capture (CDC) to track these changes in the user-defined tables. SQL Server tracks the defined table with a mirrored table with same column structure; however; it adds additional metadata fields to track these changes. We can use table-valued function to access this changed data.

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How to recognize corrupted SQL backup files

February 22, 2019 by

A Database administrator’s key task is to keep the database healthy and available for the users. We are used to taking regular SQL backups depending upon the database criticality and the recovery model. We define the Recovery Point Objective (RPO) Recovery Time Objective (RTO) or the database system, and we should be able to recover the database in any scenario to meet the requirement.

SQL Server FILESTREAM and Replication

February 19, 2019 by

In the previous articles in this series (see TOC at bottom), we wrote about the various feature of the SQL Server FILESTREAM. In SQL Server, we use replication to replicate the articles to the destination server. Consider a scenario in which we have the FILESTREAM database in our environment. We would also have the requirement to configure this database for SQL Server replication.

Export SQL Server FILESTREAM Objects with PowerShell and SSIS

February 14, 2019 by

In this series of articles on SQL Server FILESTREAM (see TOC at bottom), we explored various ways to store unstructured data in the file system with the metadata in SQL Server tables. If we have a large number of objects in the file system, it is advisable to use the fast disk for storage purpose. It is faster and provides better IO in comparison with the traditional file system.

Power BI Desktop and Python; like Peanut Butter and Chocolate

February 13, 2019 by

Power BI Desktop helps to visualize complex data with the help of inbuilt and custom visualizations. It allows integrating data from the various data sources and preparing visualization from it.

Microsoft recently integrated the Python programming language in the Power BI. Python is a powerful object-oriented language and is used by the data analyst and scientist to analyze complex datasets. We can now use the Python as a preview feature in the Power BI August 2018 release onwards. We can now use Python scripts to generate custom visualization. The combination of these technologies is akin to 1 + 1 = 3 or like the famous ad for Reese’s Peanut butter cups, when chocolate was introduced to Peanut Butter 😉

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Importing SQL Server FILESTREAM data with SSIS packages

February 1, 2019 by

Initial configuration

We have been exploring the SQL Server FILESTREAM feature in this ongoing series of articles. In this previous article, Managing data with SQL Server FILESTREAM tables, we wrote about inserting FILESTREAM data into a FILESTREAM table and performing DML activities on it. Suppose we have created the FILESTREAM database in our instance and now we want to insert a large number of files into a FILESTREAM container. It is easy to write out the insert queries for a small number of files, but if the numbers of files were in huge quantity, it would be difficult to write out the code and insert data into it. It is difficult to manage such kind of requests regularly in the environment.

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