JsonSyntaxException: Expected a string but was BEGIN_ARRAY closes apache/incubator-predictionio#445
Project: http://git-wip-us.apache.org/repos/asf/predictionio/repo Commit: http://git-wip-us.apache.org/repos/asf/predictionio/commit/865d24cb Tree: http://git-wip-us.apache.org/repos/asf/predictionio/tree/865d24cb Diff: http://git-wip-us.apache.org/repos/asf/predictionio/diff/865d24cb Branch: refs/heads/master Commit: 865d24cb4838dc30d0fa746e8e17823adf1c2de4 Parents: e1b211e Author: Jeffrey Cafferata <[email protected]> Authored: Mon Nov 20 16:30:39 2017 +0900 Committer: Takahiro Hagino <[email protected]> Committed: Mon Nov 20 16:30:39 2017 +0900 ---------------------------------------------------------------------- .../templates/ecommercerecommendation/quickstart.html.md.erb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/predictionio/blob/865d24cb/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb ---------------------------------------------------------------------- diff --git a/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb b/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb index 5907a2d..91e79c0 100644 --- a/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb +++ b/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb @@ -459,7 +459,7 @@ NOTE: You may see `appId` in engine.json instead, which means you are using old ## 6. Use the Engine -Now, You can retrieve predicted results. To recommend 4 items to user ID "u1". You send this JSON `{ "user": ["u1"], "num": 4 }` to the deployed engine and it will return a JSON of the recommended items. Simply send a query by making a HTTP request or through the `EngineClient` of an SDK. +Now, You can retrieve predicted results. To recommend 4 items to user ID "u1". You send this JSON `{ "user": "u1", "num": 4 }` to the deployed engine and it will return a JSON of the recommended items. Simply send a query by making a HTTP request or through the `EngineClient` of an SDK. With the deployed engine running, open another terminal and run the following `curl` command or use SDK to send the query:
