Recent Blogs...

-s Flavours such as EKS or AKS. To achieve end goal it is required to intract with database using Go. In this Blog I’ll showcase that we can use the Go-ORM or GORM to interact with a sqlite3/Postgres database in a simple manner. ORMs or Object Relati

-issue. And as always AWS documentation is super confusing when we need something that is important. We can get better results outside the aws documentation and I dont remember aws documentation has solved any problem for me last time. But anyways let

-erence and links have been taken from the official Keycloak documentation, which can be accessed from keycloak website. Before seeing how to configure the keycloak Customers to be able to implement this authorization strategy, we are going to name a

-supply in your home(Should read if you have frequent power outages). Application: I have been having many power outages in my place and it is frustrating when there is a power outage and the AC goes off and I need to manually switch on the fan, that

-ak. This blog will give we a gentle introduction without going too much into detail. Even if we are new to these standards, we may still want to skim through them. Authorizing application access with OAuth 2.0 OAuth 2.0 is by now a massively popular

-ith a proof-of-concept (poc) of running Postgres Cluster on ARM based Graviton ec2 in aws cloud. We will proceed through the running of multi-architecture Docker images to leverage the latest AWS Graviton2 processors. The AWS projected performance an

-ive you below the links in order to create and run keycloak application. I am using steps defined in the below codecentric helm repo for installing the application. Download the values.yaml and make changes related to ingress. I’ll update the values

-nd CloudFormation always leading me to the error below:- I found it surprising that there wasnt a single google result revealing the actual cause of this error and by hit and trial method I have come up with a solution. The below document does not t

-ut when we create an application using OCI enabled helm ecr repository in ArgoCD we face issues. The version of ArgoCD is v2.0.5. This is the command that I use to create an application in the ArgoCD using a helm chart stored in the OCI registry as a

-Helm chart. below is one of the many scenarios and others can be solved by just updating the Helm chart. In case you would like to know what is OCI and how to install add charts into the ecr repo please visit my other blog Helm OCI based charts into

-ted the development effort on our Helm charts. This article will show you how to create, push and pull helm chart into the AWS ecr repository. Also will showcase if you face any error related to ocr what necessary steps you need to take in order to r

- application as a web application in your Cloud environment and the steps involved on how to install pgAdmin on Kubernetes using Helm Chart. For documentations on pgAdmin visit the official website. My web application developers required access to t

-that can be sensitive. So if you are seeing the below warning from helm chart you are one of them:- WARNING: Kubernetes configuration file is group-readable. This is insecure. Location: /home/mukesh/.kube/config WARNING: Kubernetes configuration fil

- for Azure Git Repository, please follow the below steps:- A personal access token (PAT) is used as an alternate password to authenticate into Azure DevOps. Learn how to create, use, modify, and revoke PATs for Azure DevOps. Sign in to your organiz

-tist, I would encourage you to switch you to Jupyter Lab. For Jupyter Lab installation steps go here Below are some of the advantages that I see using Jupyter Lab over Jupyter Notebook:- The new terminal is a tab view to use compared.

-(last-in, first-out rule). To append a member to the top of the stack you can use append(). To remove a member from the top of the stack, you can use pop() (Note: you do not need to include parameters). Examples are as follows:

-h the function names and output is same what we have in Scala, syntax in Pyspark is different on RDD operations. Ill explain here Pyspark RDD using a different approach and with a different perspective to solve the problem. Let us consider we are st

-sing the following example:

-ing power to computing infrastructure, applications, business processes to personal collaboration — can be delivered to you as a service wherever and whenever you need. Cloud databases are web-based services, designed for running queries on structur

-unstructured data at rest and data in motion. HDFS Encryption implements transparent, end-to-end encryption of data read from and written to HDFS, without requiring changes to application code. Centralized encryption and key management: A centralize

-doop platform to build, to address the needs of different scenarios. For example, Hadoop Hive is a data warehouse tools, data files stored on HDFS distributed file system can be mapped to a database table and provides SQL queries. Hive execution eng

-o the GPU to take advantage of the powerful GPU parallel execution ability to complete the data task. The combination of few number of core processors, RAM bandwidth, and the GPU has a unique advantage. GPUs typically have hundreds of processor cores

-grained control of what the transaction system can do. Having full control on the client side not only allows you to make the best decisions for optimizing for specific use cases, but it also makes integration with third-party systems simpler. Secon

-with almost 20 to 25 applications. Whenever i start working first i have to understand each applications naming convention and i keep thinking why we all not follow single naming convention. As Hadoop is evolving rapidly therefore would like to share

-n Article This article is first series of three articles, next coming articles with some code and mechanism present in latest version of HBase supporting HBase Replication. HBase Replication Hbase Replication solution can solve the cluster secur

-s intuitive and simple way to ensure the safety of the application. Software design is generally based on user stories to achieve, that is, based on how users interact with the system to design the user interface or service API. For example, a user

- 2.6.0 introduced a new feature heterogeneous storage. Heterogeneous storage can be different according to each play their respective advantages of the storage medium to read and write characteristics. This is very suitable for cold storage of data.

-with NoSQL is distributed environment are sharding and partitions. Let’s dive into ACID properties of database and CAP theorem for distributed system. The ACID properties and the CAP theorem are two concepts in data management to distributed system

- in all workflows that have a Hive action. This property will make sure that the hive job runs with the necessary number of reducers instead of just 1.HQL items : Setting properties: Keep the set properties in the HQL to a minimum. Let it take the d

-ith couple of migration projects found few business rules that need to transform to Hive compatible (some of them are very complex and nearly impossible). Solution is HPL/SQL (formerly PL/HQL), is a language translation and execution layer developed

-docs/current/connector/hive.html. An overview of our architecture is Presto is running on a different machine (Presto Machine) use Hive connector to communicate with Hadoop cluster which is running on different machines. Presto Machine have hive.prop

-e and file size should be as per the block size. HDFS is really not designed for many small files. For each file, the client has to talk to the namenode, which gives it the location(s) of the block(s) of the file, and then the client streams the dat

-hen there is need for building a real-time processing system as Kafka is a high-performance publisher-subscriber-based messaging system with highly scalable properties. Traditional systems unable to process this large data and mainly for offline used

-f extra life compared to men). I am not subject matter expert but some questions around me lead to dig more and get few possible connections to life. Hope you’ll enjoy this article to have more understanding of life(after all we all have one). Below

-ions consisting of many computational tasks across many worker machines. Eventually the big data exports around the world have derived the specialized systems on top of Hadoop to solve certain problems like graph processing, implementation of effici

-ed in system. Hive is a data warehouse software best suited for OLAP (OnLine Analytical Processing) workloads to handle and query over vast volume of data residing in a distributed storage. The Hadoop Distributed File System (HDFS) is the ecosystem

-ject on data analysis and detail description on technology used Python(web scraping- data collection), Hadoop, Spark and R. Data analysis is a highly iterative and non-linear process, better reflected by a series of cyclic process, in which informati

-ve some of our data stored in a database and other data stored on file shares with proper permissions.” This isn’t data management…it’s data storage. If you and/or your organization don’t have good, clean data, you are most definitely not ready for m

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