docs: add note on compound executor (#3406)

Co-authored-by: Han Xiao <han.xiao@jina.ai>

docs/advanced/experimental/compound_executors.md

@@ -0,0 +1,64 @@
+(compound-executor)=
+
+# Compound Executors
+
+A "Compound" Executor is a special pattern of composing Executor. It glues multiple Executors into one Executor class.
+This allows developers to leverage the feature of multiple Executors while keeping their original implementations *
+as-is*.
+
+Here are some examples in practice:
+
+- combining a Storage and a Search Indexer in one, for easier access, scaling etc.;
+- combining a custom ranker and an Indexer in one, for cases where `top_k` is not achieved after a ranking process
+  filters out results;
+- having Indexers that store multiple level of granularity in one Executor, for easier lookup and custom logic.
+
+A Compound Executor can be also seen as a monolith counterpart of the microservice design. A Compound Executor,
+regardless how many sub-Executors it contains, is normally **located in one process**; hence it can only be scaled in/out jointly.
+
+## Example
+
+In this example, I will show you how to build a Compound Indexer. I will combine a Storage Indexer and a Searcher Indexer
+into one Executor class.
+
+First, I follow the guide to create a new Executor, using `jina hub new`. See {ref}`here <create-hub-executor>` for more
+info. Then, I copy the classes [`MongoStorage`](https://hub.jina.ai/executor/3e1sp6fp)
+and [`AnnoySearcher`](https://hub.jina.ai/executor/wiu040h9) from their respective repositories.
+
+```{caution}
+If you want to develop a Compound Executor based on existing Executors in Jina Hub, 
+you have to copy-paste the code of the classes into your own Executor's package, like what I did below.
+
+This is not recommended practice in Python. This is because, for now, the Executors in Jina Hub can **not** be imported as Python modules.
+
+It is, however, outside the scope of this tutorial, to show you how to organize a Python module. Do as you see fit.
+```
+
+```python
+from jina import Executor, requests, DocumentArray
+
+
+class MongoDBStorage(Executor):
+    ...  # copied from https://hub.jina.ai/executor/3e1sp6fp
+
+
+class AnnoySearcher(Executor):
+    ...  # copied from https://hub.jina.ai/executor/wiu040h9
+
+
+class CompoundExecutor(Executor):
+    def __init__(self, **kwargs):  # you args go here
+        super().__init__(**kwargs)  # you still need to initialize the base class, Executor
+        self._storage = MongoDBStorage(**kwargs)  # other args could be passed here
+        self._vector_searcher = AnnoySearcher(**kwargs)  # same
+
+    @requests(on='/search')
+    def search(self, docs: DocumentArray, **kwargs):  # we combine the logic in one place
+        results = self._vector_searcher.search(docs, **kwargs)
+        # here you would put any other custom logic you have
+        return self._storage.search(results, **kwargs)
+```
+
+You can then continue adding custom endpoints as you want.
+
+The usage of `CompoundExecutor` is no different from the normal Executor.

docs/advanced/experimental/index.md

@@ -17,4 +17,5 @@ That said, have fun!
 
 kubernetes
 indexers
+compound_executors
 ```

docs/advanced/experimental/indexers.md

@@ -27,6 +27,8 @@ Compound indexer usually made up of a vector-based searcher, for computing the m
 Example Hub Executors:
  - [FaissLMDBSearcher](https://hub.jina.ai/executor/g57rla9l)
  - [FaissPostgresSearcher](https://hub.jina.ai/executor/nflcyqe2)
+ 
+ If you want to develop one like these, check the guide {ref}`here <compound-executor>`.
 ```
 
 ```{tip}