chore: import upstream snapshot with attribution

2026-07-13 12:25:07 +08:00
commit a26e856398
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+# Server-only
+
+<img src="./architecture.sub3.svg" />
+
+_For extremely large datasets with a small number of concurrent users._
+
+The dataset is instantiated in-memory with a Python or Node.js server, and web
+applications connect virtually. Has very good initial load performance, since no
+data is downloaded. Group-by and other operations will run column-parallel if
+configured.
+
+But interactive performance is poor, as every user interaction must page the
+server to render. Operations like scrolling are not as responsive and can be
+impacted by network latency. Web applications must be "always connected" to the
+server via WebSocket. Disconnecting will prevent any interaction, scrolling,
+etc. of the UI. Does not use WebAssembly.
+
+Each connected browser will impact server performance as long as the connection
+is open, which in turn impacts interactive performance of every client. This
+ultimately limits the horizontal scalabity of this architecture. Since each
+client reads the perspective `Table` virtually, changes like edits and updates
+are automatically reflected to all clients and persist across browser refresh.
+Using the same Python server as the previous design, we can simply skip the
+intermediate WebAssembly `Table` and pass the virtual table directly to `load()`
+
+```javascript
+const websocket = await perspective.websocket("ws://localhost:8080");
+const server_table = await websocket.open_table("my_table");
+
+const viewer = document.createElement("perspective-viewer");
+document.body.appendChild(viewer);
+await viewer.load(server_table);
+```