Great tutorial! Thank for covering variety of topics. It would ge great if you start putting notes, slides, references to a Github repository. In this way, other developers can also contribute.

Thanks for sharing. Good material

Thank you for very good explaination.

thank you for explaining the topic in such a simple and effective manner.

Great video! Simple example to explain complex concept - love it! Thanks. : )

Excellent explaination in a very simpler way,thank you

good explanation. better than documentations I read before

waow .. first time I opened this video.. It really made me fall in love with your teaching skills, way of communication and your kind body language ❤❤🔥🔥🔥🔥🔥.. Your are legend sir 👍👍👍

Thank you, sir! You saved my day! Nice explanation 🙏

U explains things very clearly,love your content

Great explanation, thanks for sharing knowledge, My only suggestion is to reduce repetitive statements.

Your videos are amazing

Great explanation, Redis provides bitmap data structure.

Thank you for a very good tutorial.

Super video. Thanks

Excellent explanation! Thank You!

Great Job Broo! The way you speak and explain is very clear!

Good One!

Hey, it will be great if you also share the reference materials as well. thanks

Well explained. Thank you!

Thanks from Malaysia. It is really clear.

thank you so much sir your explanation is awesome

Great explanation! Thanks so much!

Hi, nice vídeo! I would like to have it short, but without losing any content. Thanks for sharing 👍

Thanks for this video!!! Man!!! Could u do a video about an example using bitmap and b-tree together :D Have a nice day!

amazing ;)

Good One

Best explaination ever

question: if you have to go row by row in the bitmap index to find the matches, how is it different than a fullscan?

Hey, you explained Bitmap indexing concept really well 👍🏻. Do you have one for cluster indexing?

How about to have a session discussing about the design distributed message queue system?

Thanks You!

Thank u very much

As for as oracle , the definition for cardinality is some what not same as you explained , but your explanation of bitmap is good

thank you sir. it is really helpful. could you please suggest me a reference paper or book for this?

Question: What if any record from table is deleted ? Just turning that bit to 0 would not work much, as query could be number of users who are not approved, which in turn can include deleted users as well

Do some live with us!!!!!

soo splendid, but what if the capacity (number of rows in the database) grows, so we will have bigger indexes, thus will need to interate through a larger portion of indexes?

hey! can you do a system design for Expidia?

What do you think of CrimsonDB?

crystal clear

thanks

Even if we find all 1st in bitwise array, it's O(N) ?

If we create an index like CREATE INDEX index_name ON table_name (column_name). will the database handle it automatically for BITMAP or do I have to do any extra things to use BITMAP indexing for status column?

May be the table needs a better design here. Why not pull out status and stock in their own tables and use the status_id and stock_id as columns in the main table. Integer comparisons are faster.

can you suggest the list of books plz?

Isn’t this same as columnar format the parquet uses?

What is the relationship between bitmap indexing and high dimensional indexing problem???

Hi, bro, I see you hadn't updated for nearly half a year. Are you OK?

Good content, but the volume is very low.

Hi, thanks for the video, how will the update work, if I have to update the nth element from 1 to 0, how would I seek that element without having to go through all the numbers. Also having ids in order seem to be one of the biggest requirement for this use-case, which is not possible most times.

What you described as "Cardinality" is what I learned as "data sparsity". Cardinality refers to the relationship between rows in different tables, e.g. 1 to many (1:M), 1 to 1 (1:1) or many to many (M:N).

Conventional wisdom hulds that bitmap indexes are most appropriate for columns having low distinct values--such as GENDER, MARITAL_STATUS, and RELATION. This assumption is not completely accurate, however. In reality, a bitmap index is always advisable for systems in which data is not frequently updated by many concurrent systems. In fact, as I'll demonstrate here, a bitmap index on a culumn with 100-percent unique values (a culumn candidate for primary key) is as efficient as a B-tree index. Usage of bitmap indexes is not in fact cardinality dependent but rather application dependent. SRC : www.oracle.com/technical-resources/articles/sharma-indexes.html

Why can't we use 3 numbers for each row. 0 for approved, 1 for pending, 3 for rejected.

Thanks for sharing. However this doesn't answer the following. 1) How is the bit map index updated when you add a new ID as well as add a new type called "ON HOLD". Is the index resized when it crosses a particular threshold (say 2^n -1 )? Is it a power of 2? 2) How is the complexity of the query reduced? For e.g select all products where status in ALL except rejected and stock in ALL. In this case, how are we saving on compute because we need to loop through all bitmaps on both columns. If that's the case, there's no exploitation of the fact that the cardinality of this column in reduced. For example. why not compute a bitmap for TRUE, FALSE, TRUE || FALSE, TRUE && FALSE and keep it ready as compared to just TRUE , FALSE now. We can afford to do this as the cardinality is less.

Anyone knows his twitter handle, please let me know

Great Explanation! so you explained it nicely for 6 rows and it has 6 bits but how does it scale for millions of rows. we can't have millions of bits.

Omg you could explain everything in 5 minutes instead of repeating 100 times each simple idea. And you didn't explain why it's better than seq scan, great!! (no)

Indicies, not indexes. Thought you were all geniuses?

thanks