sumitagrawl commented on code in PR #7583:
URL: https://github.com/apache/ozone/pull/7583#discussion_r1932404653


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hadoop-hdds/docs/content/design/leader-execution/leader-execution.md:
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+---
+title: Ozone Leader Side Execution 
+summary: Ozone request execution at leader side
+date: 2025-01-06
+jira: HDDS-11898
+status: draft
+author: Sumit Agrawal 
+---
+<!--
+  Licensed under the Apache License, Version 2.0 (the "License");
+  you may not use this file except in compliance with the License.
+  You may obtain a copy of the License at
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+   http://www.apache.org/licenses/LICENSE-2.0
+
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+  distributed under the License is distributed on an "AS IS" BASIS,
+  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  See the License for the specific language governing permissions and
+  limitations under the License. See accompanying LICENSE file.
+-->
+
+# Background
+
+Here is the summary of the challenges:
+
+- The current implementation depends on consensus on the order of requests 
received and not on consensus on the processing of the requests.
+- The double buffer implementation currently is meant to optimize the rate at 
which writes get flushed to RocksDB but the effective batching achieved is 1.2 
request (on average) at best. It is also a source of continuous bugs and added 
complexity for new features.
+- The number of transactions that can be pushed through Ratis currently caps 
out around 25k.
+- The Current performance envelope for OM is around 12k transactions per 
second. The early testing with prototype for this feature pushes this to 40k 
transactions per second.
+
+## Execution at leader node needs deal with below cases
+1. Parallel execution: Currently, ratis serialize all the execution in order. 
With this new feature, it is possible to execute the request in parallel which 
are independent.
+2. Optimized locking: Currently, Locks are taken at bucket level for both read 
and write flow. With this new feature, focus to remove lock between read and 
write flow, and have more granular locking.
+3. Cache Optimization: Currently, Cache are maintained for write operation and 
read also make use of same for consistency. This creates complexity for read to 
provide accurate result with parallel operation. With this new feature, its 
planned to remove this Cache.
+4. Double buffer code complexity: Currently, Double buffer provides batching 
for db update. This is done with ratis state machine and induces issues 
managing ratis state machine, cache and db updates. With this new feature, its 
planned to remove Double Buffer.
+5. Request execution flow optimization: With new feature, its planned to 
optimize request execution flow, removing un-necessary operation and improve 
testability.
+6. Performance and resource Optimization: Currently, same execution is 
repeated at all nodes, and have more failure points. With this new feature, its 
going to add parallelism in execution, and will improve performance and 
resource utilization.
+
+### Object ID generation
+Currently, the Object ID is tied to Ratis transaction metadata. This has 
multiple challenges in the long run.
+
+- If OM adopts multi Ratis to scale writes further, Object IDs will not longer 
be unique.
+- If we shard OM, then across OMs the object ID will not be unique.
+- When batching multiple requests, we cannot utilize Ratis metadata to 
generate object IDs.
+
+Longer term, we should move to a UUID based object ID generation. This will 
allow us to generate object IDs that are globally unique. In the mean time, we 
are moving to a persistent counter based object ID generation. The counter is 
persisted during apply transaction and is incremented for each new object 
created.
+
+## Prototype Performance Result:
+
+| sno | item                                     | old flow result             
  | leader execution result |
+|-----|------------------------------------------|-------------------------------|------------------------|
+| 1   | Operation / Second (key create / commit) | 12k+                        
  | 40k+                   |
+| 2   | Key Commit / Second                      | 5.9k+                       
  | 20k+ (3.3 times)       |
+| 3   | CPU Utilization Leader | 16% (unable to increase load) | 33%           
         |
+| 4   | CPU Utilization Follower | 6% above                      | 4% below    
           |
+
+Refer [performance prototype result](performance-prototype-result.pdf)
+
+# Leader execution
+
+![high-level-flow.png](high-level-flow.png)
+
+Client --> OM --> Gatekeeper ---> Executor --> Batching (ratis request) 
--{Ratis sync to all nodes}--> apply transaction {db update}
+
+
+### Gatekeeper
+Gatekeeper act as entry point for request execution. Its function is:
+1. orchestrate the execution flow
+2. granular locking
+3. execution of request
+4. validate om state like upgrade
+5. update metrics and return response
+6. handle client retry / replay of request
+7. managed index generation (remove dependency with ratis index for objectId)
+
+### Executor
+This prepares context for execution, process the request, communicate to all 
nodes for db changes via ratis and clearing up any cache.
+
+### Batching (Ratis request)
+All requests executed in parallel are batched and send as single request to 
other nodes. This helps improve performance over network with batching.
+
+Batching of Request:
+- Request 1..n are executed and db changes are identified and added to queue 
(and request will be waiting for update via ratis over Future waiting)
+- Batcher will retrieve Request 1..n and db changes, merge those request to 
single Ratis Request message
+- Send Merged Request message to all nodes via ratis and receive reply
+- Batcher will reply to each request 1..n with db update success notifying 
future object of each request.
+
+There are multiple batchers waiting over queue,
+- As soon as queue have entry, and the batcher is available, it will pick all 
request from queue for processing
+- batcher will be un-available when its processing the batch, i.e. merge 
request and send to ratis and then waiting for reply
+
+As performance Test result, Number of batcher with "5->8" performed the best. 
+- Higher number of batcher reduces the effective batching, and performance 
reduces
+- Lower number of batcher reduces throughput as more request will be waiting 
for ratis response
+
+### Apply Transaction (via ratis at all nodes)
+With new flow as change,
+- all nodes during ratis apply transaction will just only update the DB for 
changes.
+- there will not be any double buffer and all changes will be flushed to db 
immediately.
+- there will be few specific action like snapshot creation of db, upgrade 
handling which will be done at node.
+- And response to client will be returned after the apply transaction is 
success to the nodes in quorum.
+
+## Description
+
+### Index generation
+
+In old flow, ratis index is used for `object Id` of key and `update Id` for 
key update.
+For new flow, it will not depend on ratis index, but will have its own 
**`managed index`**.
+
+Index initialization / update:
+- First time startup: 0
+- On restart (leader): last preserved index + 1
+- On Switch over: last index + 1
+- Request execution: index + 1
+- Upgrade: Last Ratis index + 1  (This is only for existing cluster during 
upgrade)
+
+Om is going to maintain `IndexGenerator` which will maintain,
+- index: Atomic long, which will generate new index using incrementAndGet()
+- commitIndex: This is saved index in DB at follower and leader. This will be 
used to update `index` when a follower becomes Leader on ratis's 
notifyLeaderChanged.

Review Comment:
   Here if follower's commit index is behind than other two nodes, than 
implicitly, ratis index will be also behind as those transactions are not 
executed. So ratis will try to select leader with most current index as I know.
   
   From behavior perspective, there is no change as commit index change is 
linked to ratis index changes implicitly. Leader election and data which is 
given preference will be dependent on ratis logic.
   
   No change will be observed with the above change, just object generation 
index is separated out.



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