mohon

History is clear on this: if left to their own devices, speculators will destroy the economy

Are you talking about the 2008 financial crisis? or do you mean something else?

I see. What's the catch on Hydra.so in terms of CAP theorem? I assume it's the C one, especially the docs mentioned about read replica. Is there any drawbacks/tradeoff that user should be aware of?

You're welcome. I think for the write part, it's always back to the old classic consensus. In then end there always that distributed voting mechanism to decide the write order

Kudos for the product launch. A bit curious on the product itself, to me the product seems similar to what Neon team does, except Neon doesn't touch the columnar/analytics and just focus on the rowstore. I'm wondering how do you position the product, if let say Neon team (after Databricks acq) decides to support the columnstore format?

They keep using the core Postgre while they touch the storage layer to works with S3. Can try ro read more here https://jack-vanlightly.com/analyses/2023/11/15/neon-serverl...

basically they separate the compute and storage into different components, where the traditional PG use both compute and storage at the same server.

because of this separation, the compute (e.q SQL parsing, etc) can be scaled independently and the storage can also do the same, which for example use AWS S3

so if your SQL query is CPU heavy, then Neon can just add more "compute" nodes while the "storage" cluster remain the same

to me, this is similar to what the usual microservice where you have a API service and DB. the difference is Neon is purposely running DB on top of that structure

especially with the push of whatsapp business, orgs can freely store ur messages to them.

also by relying on the whatsapp metadata (the one where you can export by urself), it should be already good enough for feds agent to locate u.

for the E2E itself, as non crypto guy, seems the open whisper paper implemented on whatsapp alr good enough?

I rmb someone posted a VSCode plugin where you can achieve similar mode, have multiple windows arranged inside like playing the cards in Solitaire.

Good explanation. Quick follow up, so to resolve this issue, what I have in mind are :

1. Make sure the redirect url is a valid harvestapp.com (more checks on state)

2. Encrypt the state since the start of the request, so then they can double check the state hasn't been forged by decrypt and compare

Is there any option beside those?

Me too, I'm wondering why they decided to switch immediately. Why not provide user with a toggle to switch between old and new UI, then they can see how the data says

me too, always learn something new everyday. thanks HN!

I think what OP meant is subscribe youtube premium

Is the permission also use Zanzibar? or is it using a different thing?

If I only have order_count, net_gmv and gmv and then 1 month later I want to add avg_user_session, then what I understand is we need to backfill the `session_time` to the 'main' table and do the "avg(session_time) group by user_id" to the final table.

Or are you saying that we can just create another similar table with only avg_user_session and then join by the dimension key?

Yes, we've done some benchmarks using Clickhouse with the same design that you just mentioned (1 single table that contains all relevant dimensions and metrics)

In our benchmark, we tried aggregating around 1 billion rows of raw data (2 months data) using count exact distinct -> could achieve around 50-60 seconds. If we use the HLL, the query can be finished around 20-30 seconds.

For the retention part, we're planning to keep it 1 year of data, so around 6 billion rows.

Thanks for the SEC reference!

Regarding the 1st point, let say I already have the process implemented in place. If I want to add new common column, is there a better way to easily add new common metrics/dimension without doing backfill?

Exactly. The reason I dont want to create a view is the view will incurr a lot of time being spent to just querying the same thing, making the user wait for it to finish (all of our tables are in Hive). If I use a materialized view or another table, the user just need to do 'select * from xxx' and get the report immediately.

I've experimented with OLAP engine such as Clickhouse and its view, so far looks good but need a lot of investment upfront to maintain it

I guess the way you mentioned is the only way we can do and we'll try to optimize from that

Cheers!

Is it because of company focus on VR/AR or due to slow growth?

Could you also translate the last section too? Would love to read that as well

I'm curious, how do you setup your deployment and the scale of Flagr? The only thing I could found is this [0]

[0] https://github.com/checkr/flagr/issues/139#issuecomment-4028...