Craft and publish engaging content in an app built for creators.
NEW
Publish anywhere
Post on LinkedIn & Mastodon too. More platforms coming soon.
Make it punchier 👊
Typefully
@typefully
We're launching a Command Bar today with great commands and features.
AI ideas and rewrites
Get suggestions, tweet ideas, and rewrites powered by AI.
Turn your tweets & threads into a social blog
Give your content new life with our beautiful, sharable pages. Make it go viral on other platforms too.
+14
Followers
Powerful analytics to grow faster
Easily track your engagement analytics to improve your content and grow faster.
Build in public
Share a recent learning with your followers.
Create engagement
Pose a thought-provoking question.
Never run out of ideas
Get prompts and ideas whenever you write - with examples of popular tweets.
@aaditsh
I think this thread hook could be improved.
@frankdilo
On it 🔥
Share drafts & leave comments
Write with your teammates and get feedback with comments.
NEW
Easlo
@heyeaslo
Reply with "Notion" to get early access to my new template.
Jaga
@kandros5591
Notion 🙏
DM Sent
Create giveaways with Auto-DMs
Send DMs automatically based on engagement with your tweets.
And much more:
Auto-Split Text in Posts
Thread Finisher
Tweet Numbering
Pin Drafts
Connect Multiple Accounts
Automatic Backups
Dark Mode
Keyboard Shortcuts
Creators love Typefully
150,000+ creators and teams chose Typefully to curate their Twitter presence.
Marc Köhlbrugge@marckohlbrugge
Tweeting more with @typefully these days.
🙈 Distraction-free
✍️ Write-only Twitter
🧵 Effortless threads
📈 Actionable metrics
I recommend giving it a shot.
Jurre Houtkamp@jurrehoutkamp
Typefully is fantastic and way too cheap for what you get.
We’ve tried many alternatives at @framer but nothing beats it. If you’re still tweeting from Twitter you’re wasting time.
DHH@dhh
This is my new go-to writing environment for Twitter threads.
They've built something wonderfully simple and distraction free with Typefully 😍
Santiago@svpino
For 24 months, I tried almost a dozen Twitter scheduling tools.
Then I found @typefully, and I've been using it for seven months straight.
When it comes down to the experience of scheduling and long-form content writing, Typefully is in a league of its own.
Luca Rossi ꩜@lucaronin
After trying literally all the major Twitter scheduling tools, I settled with @typefully.
Killer feature to me is the native image editor — unique and super useful 🙏
Visual Theory@visualtheory_
Really impressed by the way @typefully has simplified my Twitter writing + scheduling/publishing experience.
Beautiful user experience.
0 friction.
Simplicity is the ultimate sophistication.
Queue your content in seconds
Write, schedule and boost your tweets - with no need for extra apps.
Schedule with one click
Queue your post with a single click - or pick a time manually.
Pick the perfect time
Time each post to perfection with Typefully's performance analytics.
Boost your content
Retweet and plug your posts for automated engagement.
Start creating a content queue.
Write once, publish everywhere
We natively support multiple platforms, so that you can expand your reach easily.
Check the analytics that matter
Build your audience with insights that make sense.
Writing prompts & personalized post ideas
Break through writer's block with great ideas and suggestions.
Never run out of ideas
Enjoy daily prompts and ideas to inspire your writing.
Use AI for personalized suggestions
Get inspiration from ideas based on your own past tweets.
Flick through topics
Or skim through curated collections of trending tweets for each topic.
Write, edit, and track tweets together
Write and publish with your teammates and friends.
Share your drafts
Brainstorm and bounce ideas with your teammates.
NEW
@aaditsh
I think this thread hook could be improved.
@frankdilo
On it 🔥
Add comments
Get feedback from coworkers before you hit publish.
Read, Write, Publish
Read, WriteRead
Control user access
Decide who can view, edit, or publish your drafts.
Let's understand Hadoop Distributed File System (HDFS).
1️⃣ What is HDFS?
2️⃣ Assumptions and Goals of HDFS.
3️⃣ Namenode & Datanode.
4️⃣ Data Replication.
🧵
1️⃣ What is HDFS?
It is one of the core Hadoop components for distributed storage.
It is highly fault-tolerant and is designed to be deployed on low-cost hardware, providing high throughput access to application data and is suitable for applications that have large data sets.
2️⃣ Assumptions and Goals of HDFS
⭐ Hardware failure is the norm rather than the exception.
Any running HDFS servers can go down at any time, making it an essential goal for HDFS to be fault tolerant and recover automatically and quickly.
⭐ Applications running on HDFS need streaming access to the data
HDFS is designed more for batch processing rather than interactive use by users.
The emphasis is on the high throughput of data access rather than the low latency of data access.
⭐ Applications running on HDFS have large data sets.
It should provide high aggregate data bandwidth and scale to hundreds of nodes in a single cluster.
It should support tens of millions of files in a single instance.
⭐ HDFS applications need a write-once-read-many access model for files
A file once created, written, and closed need not be changed except for appends and truncates.
This simplifies data coherency issues and enables high throughput data access.
⭐ Moving Computation is Cheaper than Moving Data
It is often better to migrate the computation closer to where the data is located rather than moving the data to where the application is running.
This minimizes network congestion and increases overall throughput of the system.
⭐ Portability Across Heterogeneous Hardware and Software Platforms
HDFS has been designed to be easily portable from one platform to another.
This facilitates the widespread adoption of HDFS as a platform of choice for a large set of applications.
3️⃣ Namenode and Datanodes
HDFS follows a master/slave architecture where a master (namenode) manages the slaves (datanode).
There is 1 namenode per HDFS cluster and usually, 1 datanode per node in the HDFS cluster.
Namenode manages the file system namespace and regulates access to files by clients.
Datanode manages the storage for the nodes that they run on.
Internally, each file in HDFS is split into blocks and these blocks are stored in a set of datanodes.
Namenode determines this mapping of blocks to the datanode.
Datanodes serve read/write requests from the file system's client.
Datanodes also perform block creation/deletion and replication upon instruction from namenode.
Architecture is designed in such a way that any user data will never flow through namenode.
4️⃣ Data Replication
Each file is stored as a sequence of blocks and these blocks are replicated across the datanodes for fault tolerance.
The default size of a block is 128 MB. (Hadoop 2.0+)
Both, the replication factor and the block size can be configured per file.
Namenode makes all decisions regarding the replication of blocks. It periodically receives heartbeats and blockreports from datanodes (default = 3 sec).
Here's a screenshot of a blockreport:
If heartbeats from a datanode are not received for up to 10 mins (by default) to the namenode, that datanode is assumed to be dead.
In such a case, namenode will remove the record of the dead datanode, leading to under-replicated blocks...
These blocks will be replicated in existing datanodes even if they already have that block, to maintain the replication factor for the block.
That's it for today!
Here are a few questions that still remain:
How are the blocks assigned to the datanodes? and in what sequence are they written into them? What if the block gets corrupted?
Let's answer these questions in future threads.
Thanks for reading! 👋