Author: author

From Regulation to Responsibility: Understanding the EU’s AI regulation

Posted on by sanjeeva

Introduction Artificial Intelligence (AI) has rapidly transformed various aspects of our lives, from personalized recommendations to autonomous vehicles. However, with great power comes great responsibility. The European Union (EU) recognizes the need to strike a balance between fostering AI innovation and safeguarding fundamental rights. On March 13, 2024, the EU took a significant and bold step Read more about From Regulation to Responsibility: Understanding the EU’s AI regulation[…]

The World of Generative AI: An Introductory Exploration

Posted on by sanjeeva

Generative AI! If you’ve ever marveled at a piece of artwork created by an AI, or interacted with a chatbot that seemed almost human, then you’ve already had a glimpse into what Generative AI can do. Welcome to this fascinating world of Gen AI! Generative AI is a subset of artificial intelligence that focuses on Read more about The World of Generative AI: An Introductory Exploration[…]

Optimizer Access Paths: index unique scan

Posted on by sanjeeva

In our previous blog, we have talked about the optimizer access path. In the last few blogs, we have explained different access paths. In this blog, we will see how the index unique scan works. Index unique scan is the optimizer access path where the database returns at most one row. It reads the index Read more about Optimizer Access Paths: index unique scan[…]

Optimizer Access Paths : Fast Full Scan

Posted on by sanjeeva

An index fast full scan reads the entire index as it is i.e. as it exists on the disk. This index read is unsorted. This access path usage multiblock IO to perform the index scan. Index fast full scan simply reads all of the leaf, branch and root block of index quickly using multiblock IO Read more about Optimizer Access Paths : Fast Full Scan[…]

Data Replication Setup Using Master and Slave: PostgreSQL- IV

Posted on by sanjeeva

This is last and final blog on Master-Slave replication in PostgreSQL database. In last blog, we have seen Async node setup. We are exploring Sync node in this blog. We will use the same automation script for Sync node also with two changes in master and one change in slave configuration. Let’s start with master. Read more about Data Replication Setup Using Master and Slave: PostgreSQL- IV[…]

Data Replication Setup Using Master and Slave: PostgreSQL- III

Posted on by sanjeeva

In last few blogs, we have seen how to automate steps required to setup Master-slave nodes. This blog would be the last in this series. Until now we have discussed how the architecture should look like and what parameters are needed to be modified to what value on master and slave node. In this blog, Read more about Data Replication Setup Using Master and Slave: PostgreSQL- III[…]

PostgreSQL Meta-Command using psql: Command Information -IV

Posted on by sanjeeva

This is in continuation of My last blog about Meta Commands in PostgreSQL. In last blog I have explained what a Meta command and how to list databases. In next few blogs we will explore few of Meta commands. Lets start exploring schemas. Visit this series of last blog for other command. The command we Read more about PostgreSQL Meta-Command using psql: Command Information -IV[…]

Data Replication Setup Using Master and Slave: PostgreSQL – I

Posted on by sanjeeva

In last few blogs, we have seen how to automate steps required to setup Master-slave nodes. In next few blogs we will explore how High Availability(HA) will be setup. In this blog we will talk about how the architecture look like. To achieve HA in the PostgreSQL database, we should setup a Master-Slave replication environment Read more about Data Replication Setup Using Master and Slave: PostgreSQL – I[…]

Data Replication Setup Using Master and Slave: PostgreSQL – II

Posted on by sanjeeva

In last few blogs, we have seen how to automate steps required to setup Master-slave nodes. In next few blogs we will explore how High Availability(HA) will be setup. We can implement this master-slave environment on separate VMs. We can also implement this on the same machine. For blogging purposes, we will use the same machine for Read more about Data Replication Setup Using Master and Slave: PostgreSQL – II[…]

Optimizer Access Paths : Direct Path Read

Posted on by sanjeeva

In usual business, Oracle reads data from data files into the buffer cache of SGA. A Read request is served from there to the client. However, A direct path read is where the data is read directly from the data files into the PGA rather than into the buffer cache in the SGA. Direct Path Read more about Optimizer Access Paths : Direct Path Read[…]

Optimizer Access Paths : What is Index Full Scan

Posted on by sanjeeva

Index full scan is the optimizer access path where the database reads the index from start to end, one block at a time. It reads the index starting from the root block, navigating down using branch towards the left side, or right side if we are doing a descending full scan until it hits the Read more about Optimizer Access Paths : What is Index Full Scan[…]

Automating Master and slave replication: PostgreSQL – I

Posted on by sanjeeva

Master-slave replication setup is the implementation of HA in PostgreSQL. Deployment architecture of 1 master and at least one slave in SYNC mode would be able to provide senses of High Availability of the database. To achieve this we require some steps to be performed into the database which will make one of the nodes Read more about Automating Master and slave replication: PostgreSQL – I[…]

MVCC Concurrency Architecture: PostgreSQL way of implementation – III( pros/cons)

Posted on by sanjeeva

We have explored the PostgreSQL implementation of MVCC in the last two blogs. We will understand the pros and cons of this way of implementation in this blog. This implementation avoided the need for locking of a tuple for any possible updates because the updates are not in-place. Updates in PostgreSQL are creating a complete Read more about MVCC Concurrency Architecture: PostgreSQL way of implementation – III( pros/cons)[…]

PostGIS Installation with PostgreSQL

Posted on by sanjeeva

PostgreSQL supports many other tools in form of database extensions like UUID support, dblink. In the same way, it also supports geographic and spatial data with help of PostGIS. This blog will explain how to install PostGIS 2.5 which can be used by PostgreSQL 11. There are many version of this spatial extension of database Read more about PostGIS Installation with PostgreSQL[…]

What is a Database Cluster: PostgreSQL

Posted on by sanjeeva

In the last blog, we have installed PostgreSQL on different Linux platforms ( CentOs, Ubuntu). However, We have leftover to initialize the installation and connection to the database that we will discuss here. Postgres provides more than one way to initialize a database cluster. We will use pg_createcluster in this blog. But before that, we Read more about What is a Database Cluster: PostgreSQL[…]

PostgreSQL Meta-Command using psql: Command Information -III

Posted on by sanjeeva

This is in continuation of My last blog about Meta Commands in PostgreSQL. In last blog I have explained what a Meta command and how to list databases. In next few blogs we will explore few of Meta commands. Lets start exploring schemas. Visit this series of last blog for other command. The command we Read more about PostgreSQL Meta-Command using psql: Command Information -III[…]

PostgreSQL Meta-Command using psql: Command Information -II

Posted on by sanjeeva

This is in continuation of My last blog about Meta Commands in PostgreSQL. In last blog I have explained what a Meta command is all about. In next few blogs we will explore few of Meta commands. Lets start exploring databases. The command we will explore here is:1. \l2. \c Once you connected to a Read more about PostgreSQL Meta-Command using psql: Command Information -II[…]

Optimizer Access Paths: How Index FFS works with Distinct

Posted on by sanjeeva

Distinct is the keyword that oracle used to filter out unique values from a column. However, it is very interesting to see the behavior followed by the optimizer for its access path. In this “Optimizer Access Paths” blog, we will see how we can make optimizer to use an index with a distinct keyword. Let’s Read more about Optimizer Access Paths: How Index FFS works with Distinct[…]

MVCC Concurrency Architecture: PostgreSQL way of implementation – II

Posted on by sanjeeva

This is in continuation from my last blog on PostgreSQL implementation of MVCC. We will understand transaction id (XID), versioning of a tuple (xmin & xmax) in more detail. Before we move to understand the implementation of a transaction using MVCC, let’s first understand how a tuple is created/updated/deleted. PostgreSQL assigns the current transaction id Read more about MVCC Concurrency Architecture: PostgreSQL way of implementation – II[…]

Optimizer Access Paths: How oracle database works

Posted on by sanjeeva

In this blog, we will explore what is the access path in the Oracle database. However, before moving to the access path, let’s first understand what is a row source. It is a set of rows that are returned in a step by execution plan. It can be a table or a result of join operations Read more about Optimizer Access Paths: How oracle database works[…]

Concurrency Control in PostgreSQL

Posted on by sanjeeva

In previous blog, we have detailed out about the inception of PostgreSQL. In this blog, we will explain the architecture (MVCC) with respect to PostgreSQL. Concurrency Control: There are more than one way to provide concurrency control by database. Concurrency is an important factor to allow many users to work on the same dataset at Read more about Concurrency Control in PostgreSQL[…]

PostgreSQL Meta-Command using psql: Command Information -I

Posted on by sanjeeva

This is in continuation of My last blog about Meta Commands in PostgreSQL. In last blog we have explained what a Meta command is all about. In next few blogs we will explore few of Meta commands. Let’s start with psql command itself. Once we logged in using psql, the environment should be look like Read more about PostgreSQL Meta-Command using psql: Command Information -I[…]

How To: List keys of collection MongoDB

Posted on by sanjeeva

There are many things needed in the DBA’s life for which there are no simple and straight forward ways to find out and they sometimes are tricky to find out. One of them is to find the keys of a collection. There are alternate methods we can certainly explore to retrieve all keys. the catch Read more about How To: List keys of collection MongoDB[…]

PostgreSQL Meta-Command using psql: Generic Information

Posted on by sanjeeva

In our last blog we have discussed the history of origination of PostgreSQL database. This database, like all other RDBMS, has more than one interface to connect to the database. PostgreSQL has psql program as command line interface (CLI) and PgAdmin as graphical user interface (GUI) psql as complete set of commands through which we Read more about PostgreSQL Meta-Command using psql: Generic Information[…]

PostgreSQL Installation on CentOS 7

Posted on by sanjeeva

There are multiple ways of installation of the PostgreSQL database on Unix like platforms. We will explore the installation of PostgreSQL version 12 on CentOS 7 using YUM installation. Let’s start. Verifying the version of CentOS: root@localhost yum.repos.d]# rpm -q centos-release centos-release-7-7.1908.0.el7.centos.x86_64 PostgreSQL allows us to download many version across multiple platform, one should visit its official Read more about PostgreSQL Installation on CentOS 7[…]

PostgreSQL Installation on Ubuntu

Posted on by sanjeeva

There are multiple ways of installation of the PostgreSQL database on Unix like platforms. We will explore the installation of PostgreSQL version 11 on Ubuntu 18.04 LTS using apt installation. Let’s start. Login to Ubuntu and check the version of Ubuntu. postgres@sanjeeva:/home/sanjeeva/postgres$ lsb_release -a No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 18.04.5 LTS Release: Read more about PostgreSQL Installation on Ubuntu[…]

Evolvement of PostgreSQL: Background

Posted on by sanjeeva

Research papers of “System R” from IBM were initially picked up by two professors, Michael Stonebraker and Eugene Wong, at Berkeley University, California. This resulted in a new database called INteractive Graphics REtrieval System i.e. “Ingres“. The work done by this duo for Ingres becomes the foundation of many relational databases like MS SQL Server, Read more about Evolvement of PostgreSQL: Background[…]

How To: List all indexes in MongoDB

Posted on by sanjeeva

Indexes are a very important structure in any database and the same is true with MongoDB as well. It adds spices to the performance of your query. It is also very important to know what and how many indexes are created on your DB. In the normal life of DBA, one needs to find out Read more about How To: List all indexes in MongoDB[…]

How To: Creating a collection subset from collection in MongoDB

Posted on by sanjeeva

Many a time there are required to create a new collection from existing ones with the same or different size. In this blog, we will see how to create a new collection from the existing one and with a smaller size. For Sample data, We may use Kaggle to get huge data set. In my collection, I Read more about How To: Creating a collection subset from collection in MongoDB[…]

Cloud database war: Advantage shifting to Red?

Posted on by sanjeeva

With its inception in 2006, Amazon AWS has definitely gone a long way.  Engineers from Amazon worked really-really well which has not only completely changed the horizon of cloud but also emerges as one of the boon for any business to adopt.  Although, there are many other vendors available in the cloud market and they Read more about Cloud database war: Advantage shifting to Red?[…]

WiredTiger: A game changer for MongoDB

Posted on by sanjeeva

Storage engine is one of the key component of any database.  It is, in fact, a software module which is used by database management system to perform all storage related operations e.g. create information, read information and update any information.  The term storage means both disk storage and memory storage.   Choosing right storage engine is Read more about WiredTiger: A game changer for MongoDB[…]

Data Pump: impdp

Posted on by sanjeeva

Problem Statement: Restore entire database using Data Pump. Restore table(s) Restore tablespace(s) Restore schema(s) Restore using Transportable tablespaces (TTS) Restore from multiple small sizes of dump files Restore in parallel mode Approach: There are single shot solution to all the above problem statement and it is IMPDP in Data Pump.  It is one of various Read more about Data Pump: impdp[…]

Trend of data growth in Oracle Database

Posted on by sanjeeva

In real production world “Prediction” of data growth is an important aspects of DBA life because this will allow business not only to foresee the real position in terms of existing hardware but also enable to plan the future expenses which should be spent on hardware(s) & storage. To generate data growth report, Oracle provides Read more about Trend of data growth in Oracle Database[…]

Oracle Data Pump: expdp & impdp

Posted on by sanjeeva

Problem Statement: Backup entire database using Data Pump. Backup table(s) Backup tablespace(s) Backup schema(s) Backup using Transportable tablespaces (TTS) Generate multiple small sizes of dump files Backup in parallel mode Approach: There are single shot solution to all the above problem statement and it is Data Pump.  It is one of various backup tools provided Read more about Oracle Data Pump: expdp & impdp[…]

Data Pump: a tool to backup and restore database

Posted on by sanjeeva

Among various techniques of backing up your database Oracle provides data pump as one of tool which they are constantly improving and making this tool sharper release by release. Since its first launch with 10g version, it has improved a lot not only in terms of its new features but in terms of performance as Read more about Data Pump: a tool to backup and restore database[…]

MongoDB Enterprise Edition Installation – Ubuntu

Posted on by sanjeeva

MongoDB is one of the document oriented open source database developed in c++, first come into shape in 2007 when in order to overcome the shortfall of existing database while working for an advertising company “DoubleClick” development team has decided to go further rather than struggling with database.  The team of this advertising company was Read more about MongoDB Enterprise Edition Installation – Ubuntu[…]

How to: Uninstallation of MongoDB on Ubuntu

Posted on by sanjeeva

MongoDB is one of the document oriented open source database developed in c++, first come into shape in 2007 when in order to overcome the shortfall of existing database while working for an advertising company “DoubleClick” development team has decided to go further rather than struggling with database.  The team of this advertising company was Read more about How to: Uninstallation of MongoDB on Ubuntu[…]

MongoDB Installation – Ubuntu

Posted on by sanjeeva

MongoDB is one of the document oriented open source database developed in c++, first come into shape in 2007 when in order to overcome the shortfall of existing database while working for an advertising company “DoubleClick” development team has decided to go further rather than struggling with database.  The team of this advertising company was Read more about MongoDB Installation – Ubuntu[…]

Mongo DB – An Introduction

Posted on by sanjeeva

About NoSQL:  Let’s understand about the NoSQL.  We will explore MongoDB and it’s inception later. Like any other type of database NoSQL database also provides a mechanism to store and retrieve which is modeled in such a way so that it should be different than Relational database.  In short, a NoSQL database does not store Read more about Mongo DB – An Introduction[…]

How to re-organize your data files of a tablespace

Posted on by sanjeeva

Problem statement:  How to move data files from one location to another on same storage. How to move data files from one storage to another. How to rename data files to make data file name standardized Environment / Scenario: You have a database where you have to move your data files from old slower storage Read more about How to re-organize your data files of a tablespace[…]

How to copy Multi terabyte data to another Database Server

Posted on by sanjeeva

Problem statement:  How to migrate huge data from One DB to another DB. Multi-Terabyte data loaded on one database should be copied to another database. Environment: You have multi-terabyte Database Your database is growing on daily basis, based on data feeds. Number of Indexes on these tables are very high, and thus, size of indexes Read more about How to copy Multi terabyte data to another Database Server[…]

Move DB with Oracle 11g Binaries

Posted on by sanjeeva

Problem Statement: Move DB with Oracle Binaries on New Storage Create new DEV/UAT from Production. Scenarios: While creating new UAT or DEV from production and make this version of oracle to the same patch set level as of production, there are more than to move DB with Oracle Binaries. Examples: One way to move DB Read more about Move DB with Oracle 11g Binaries[…]

How to: Speed up Inserts in database

Posted on by sanjeeva

We have written blogs which helps DBA doing their day to day works.  This blog will explain how to Speed up Inserts while loading data from huge files.  Problem Statement: The problem statement this blog is going to answers with respect to Speed up Inserts are: How to speed up loading millions of rows from Read more about How to: Speed up Inserts in database[…]

Reduce in MapReduce … Unwinding

Posted on by sanjeeva

In our previous blogs we have studied about Big data, Hadoop.  We have also explained MapReduce internal workings like how Map works using short and shuffle.  This blog is dedicated to Reduce in MapReduce. Once this shuffling completed, it is where Reduce in MapReduce come into action. Its task is to process the input provided Read more about Reduce in MapReduce … Unwinding[…]

MapReduce – Sort & Shuffle

Posted on by sanjeeva

This is in continuation of MapReduce Processing   We are going to see how the input is provided to SORT process, how this is sorted and distributed on all available DNs and this input is taken over to the next step Shuffle. This output will be input for next process which is SORT. Sort takes Read more about MapReduce – Sort & Shuffle[…]

MapReduce – Unwinding Map

Posted on by sanjeeva

In last discussion on MapReduce, we discussed the algorithm which is used by Hadoop for data processing using MapReduce. In this blog, we will discuss the specific section of MAP in MapReduce and it’s functionality. Unwinding Map We will explain this in details and with example here. Example: Lets consider our scenario : The Scenario: Read more about MapReduce – Unwinding Map[…]

MapReduce – Unwinding Algorithm

Posted on by sanjeeva

With discussion, in my last blog, about “How Hadoop manages Fault Tolerance” within its cluster while processing data, it is now time to discuss the algorithm which MapReduce uses. Name Node (NN) It is Name Node (NN) where a user submits his request to process data and submits his data files.   As soon as NN receives data Read more about MapReduce – Unwinding Algorithm[…]

MapReduce : Fault Tolerance

Posted on by sanjeeva

The Fault Tolerance: Before we see the intermediate data produced by the mapper, it would be quite interesting to see the fault tolerant aspects of Hadoop with respect to MapReduce processing. The Replication Factor: Once Name node (NN) received data files which has to be processed, it splits data files to assign it to Data Read more about MapReduce : Fault Tolerance[…]

MapReduce Internals: Philosophy

Posted on by sanjeeva

In our last few blogs we have explained what is BigData, How Hadoop evolved & MapReduce workings.  In this blog we will see the philosophy of MapReduce. The Philosophy: The philosophy of MapReduce internals workings is straight forward and can be summarized in 6 steps. The smaller, the better, the quicker: Whatever data we provide Read more about MapReduce Internals: Philosophy[…]

MapReduce : Internals

Posted on by sanjeeva

The MapReduce Framework: MapReduce is a programming paradigm that provides an interface for developers to map end-user requirements (any type of analysis on data) to code. This framework is one of the core components of Hadoop. The capabilities: The way it provides fault-tolerant and massive scalability across hundreds or thousands of servers in a cluster Read more about MapReduce : Internals[…]

HDFS Architecture : Explained

Posted on by sanjeeva

Inspired by Google’s GFS,
HDFS (Hadoop Distributed File System ) architecture has designed in such a way that it has excellent fault-tolerant and self-healing features. It enables Hadoop to harness the true capability of distributed processing techniques…..

Magic of Hadoop

Posted on by sanjeeva

Disadvantage of DWH: Because of the limitation of currently available Enterprise data warehousing tools, Organizations were not able to consolidate their data at one place to maintain faster data processing. Here comes the magic of hadoop for their rescue. Traditional ETL tools may take hours, days and sometimes even weeks.  And because of this, performances Read more about Magic of Hadoop[…]

Journey of Hadoop

Posted on by sanjeeva

History of Hadoop: At the outset of twenty-first century, somewhere 1999-2000, due to increasing popularity of XML and JAVA, internet was evolving faster than ever. This leads to the invention of Hadoop. Requirement is mother of invention: As the world wide web grew at dizzying pace, though current search engine technologies were working fine, a Read more about Journey of Hadoop[…]

Big Data: Introduction and 4V’s

Posted on by sanjeeva

Innovations in technologies made the resources cheaper than earlier.  This enables organizations to store more data at lower cost and thus increasing the size of data. Gradually the size of data becomes bigger and now it moves from Megabytes (MB) to Petabytes (1e+9 MB). This huge increase in data requires some different kind of processing.  Read more about Big Data: Introduction and 4V’s[…]