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Understand Airflow For Data Engineering (Quick Guide📝)
📌 What is Apache Airflow?
As a Data Engineer, one of the tasks you perform is to build a data pipeline now for that you can write simple Python scripts or use enterprise tools.
Simple Python script with cron job is enough for a few pipelines but what if you have 100s of them? Hard to manage!!!
This is where Airflow Comes into the picture
💡 It's an open-source tool for managing data pipelines, you can build, schedule, and monitor workflows.
In one place you can manage everything!
There are a few components you need to understand.
📌 DAG (Directed Acyclic Graph):
At the heart of Airflow is the DAG, which defines a collection of tasks and their dependencies in a specific order.
This is a core computer science concept.
Think of it as a blueprint of your workflow, ensuring that tasks run in the sequence.
👉🏻 Directed: Tasks move in a certain direction.
👉🏻 Acyclic: No loops! Tasks don't run in circles.
👉🏻 Graph: A visual representation of the tasks.
📌 What is a Task?
It is basically where you write your logic, such as reading data, transforming it, or writing it. Each task runs independently, in its own process.
To create a task we need to use Operators.
📌 What are Operators?
There are many different operators you can use for a specific task.
They determine WHAT gets done.
👉🏻 BashOperator: Executes a bash command.
👉🏻 PythonOperator: Executes a Python function.
👉🏻 PostgresOperator: Executes SQL on a Postgres database.
and many more!
📌 Executor:
Determines HOW tasks are run.
There are several types:
👉🏻 SequentialExecutor: Runs tasks sequentially.
👉🏻 LocalExecutor: Runs tasks in parallel on a single machine.
👉🏻 CeleryExecutor: Distributes tasks across multiple machines.
📌 Scheduler: The brain behind when your tasks run. It checks the DAGs and sends them to the executor to see if they have tasks to run.
📌 Web Server: A friendly UI to monitor and manage your DAGs. You can check task logs, rerun tasks, and visualize task dependencies.
Let me know if you found this helpful 👇🏻
You can watch an overview of Airflow here - https://t.co/uquIv7l36z
Discover the infinite possibilities of your data infrastructure with #OceanBase on #Kubernetes! Experience seamless fault recovery and scaling like never before🌊
#K8s#DataBase#DataTech
Why is it impossible to kill CockroachDB? ⚡
I had this question for a long time and who better to answer this than the co-founder himself? hence I hosted Ben Darnell for a deep-tech conversation on CockroachDB and Distributed Databases.
We went into details of all three layers - distributed storage, distributed execution, and the language interface of Cockroach. Two things that blew my mind were how they
1. built SQL layer on top of distributed ordered KV pairs
2. provide strong consistency even when the DB spans the entire world
give it a watch - https://t.co/vkA9u26Nt6
ps: while discussing the future of databases, Ben suggested a really interesting idea that will not only blow your mind but could inspire you to kick off an amusing open-source project.
By the way, they do have offices in Bangalore, so if you are looking to work on databases, check out their open positions. I can vouch for them :)
#DistributedDatabases #CockroachDB
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27 Websites that'll pay you $450/hr for data entry jobs:
I have prepared a list of 46 Websites that'll pay you $45/hr for data entry jobs With Just a Smartphone or Laptop and Internet.
For absolutely FREE:
To get it:
1. Follow Me
2. Like and Retweet
3. Reply with "Data”
Instant delivery guaranteed!
Did you know Rise of the Ronin has connections to Ninja Gaiden and Nioh?
Team Ninja shares insights plus first details on an upcoming update: https://t.co/DLAnzKSX7D
66 SQL Interview Questions you need to excel at to land your dream job⬇️
I am sharing my list with you today!
For absolutely FREE:
To get it:
1. Follow Me
2. Like and Retweet
3. Reply with "SQL”
#SQL#SQLLearners#InterviewQuestions
[Macam-macam JOIN pada SQL]
ini adalah materi dasar untuk perjoinan pada SQL, sebelum kamu belajar lebih lanjut tentang join beberapa tabel, kamu harus paham cara dasar menggabungkan dua tabel terlebih dahulu!
berikut contoh macam-macam join, ilustrasi beserta contohnya!
This research paper wrote by #Wuhan university, #ETH, #Ebay and #oceanbase intoduced #BenchTemp, a general Benchmark Python Library for evaluating Temporal Graph Neural Networks quickly and efficiently on various workloads, which is quite insightful👉https://t.co/36Ws8B0JPp
I would like to know the key differences of all the main-steaming distributed databases in the market like #spanner#cockroachdb, #oceanbase. Their architecture, performance, etc. Somehow it seems there's too much to discover.
This tweet seems somewhat relevant now
ChatGPT was supposed to kill our startup 1.5 years ago
There have been several other "extinction" events like Google Docs + Microsoft Word adding AI to their suite
Each time, it had literally no effect on us whatsoever, and we grew faster
👏Join us today at the #ICDE2024 in Utrecht, Netherlands!
Our CTO Chuanhui Yang will give a talk on #OceanBase's journey from distributed #OLTP to #HTAP and our newest technical insights on distributed #database.
Meet us this afternoon in Theater 12, Kinepolis Jaarbeurs theater!
📩Are you heading to #ICDE2024 ?
Stop by our booth on Tuesday, May 14 at the 40th IEEE International Conference on Data Engineering to learn more about #OceanBase and receive fun swags!
🌊See you in Utrecht! 🌊
The data engineering market will cross the $100 billion mark by 2028 📈🤩
This is the best time to get started in data engineering!
Keep reading and you'll know why 👇🏻
According to the Analytics India Magazine Research report from last year, the data engineering market was expected to surge at a Compound Annual Growth Rate (CAGR) of 33.8% over the next five years, increasing from USD 29.1 billion in 2023 to an estimated USD 124.7 billion by 2028
One of the reasons is Generetive AI or LLM, we need to covert raw data that can provide actionable insights
The report presented many different areas of Data Engineering
✅ Number of jobs available
✅ What is the median salary earned by data engineers (based on company & industry types)
✅ Attrition rate for data engineers
✅ Skills required based on years of experience
and many more...
As more and more people get internet access, a significantly large volume of data is being generated. The data is generated through several sources including sensors, transactions, social media, and others.
Data engineers play a vital role in managing the data and ensuring its quality and integrity.
I published an in-depth video explaining the complete report, you can watch it here: https://t.co/2gFgmarKIn