On Thu, Jan 26, 2017 at 11:36 AM Galen M O'Sullivan <gosulli...@pivotal.io> wrote:
> I think the reason we use JSON is because it's easy. I'm not convinced that > 90% of JSON data is from JavaScript, unless you have data to back that up > -- a lot of scripting languages use it because it's convenient. > Excuse my hyperbole. Wether the user is JavaScript, Python or whatever the issue that like, JavaScript, JSON does not have rich datatypes and trying to infer those types from the data is dangerous. JSON, YAML, etc. are only useful both sides of the persistence agree on the same schema for the types ultimately attributed to the value when parsed. Since Geode does not require you to pre-define a schema for your data we attempt to infer type information and create a structured datatype based on the inference. Then when someone wants to get that data back out we convert our inferred data to JSON and pass it back. That translation between untyped to typed back to untyped is where we get caught up. Its like passing a phrase to Google translate, passing the translation back through the way and expecting to get the same phrase, try it, it gets strange fast. For unstructured data, like JSON, we should persist the original. Doing anything else complicates the issue of the round trip result described above. If the values need to be coerced into something else, say for indexing, then it should only be done at the time of indexing or use. This is where "converters" are a natural fit. Consider indexing command, "create index foo on value.foo as type time with converter MyCustomDateConverter". The indexer would invoked java.util.Date MyCustomDateConverter.convert(Object value) when indexing that column. -Jake
