# First proposal
In order to overcome FoudationDB limitations on key size (10 kB) and value size
(100 kB) we could use the following approach.
Bellow the paths are using slash for illustration purposes only. We can use
nested subspaces, tuples, directories or something else.
- Store documents in a subspace or directory (to keep prefix for a key short)
- When we store the document we would enumerate all field names (0 and 1 are
reserved) and store the mapping table in the key which look like:
```
{DB_DOCS_NS} / {DOC_KEY} / 0
```
- Flatten the JSON document (convert it into key value pairs where the key is
`JSON_PATH` and value is `SCALAR_VALUE`)
- Replace elements of JSON_PATH with integers from mapping table we constructed
earlier
- When we have array use `1 / {array_idx}`
- Store scalar values in the keys which look like the following (we use
`JSON_PATH` with integers).
```
{DB_DOCS_NS} / {DOC_KEY} / {JSON_PATH}
```
- If the scalar value exceeds 100kB we would split it and store every part
under key constructed as:
```
{DB_DOCS_NS} / {DOC_KEY} / {JSON_PATH} / {PART_IDX}
```
Since all parts of the documents are stored under a common `{DB_DOCS_NS} /
{DOC_KEY}` they will be stored on the same server most of the time. The
document can be retrieved by using range query (`txn.get_range("{DB_DOCS_NS} /
{DOC_KEY} / 0", "{DB_DOCS_NS} / {DOC_KEY} / 0xFF")`). We can reconstruct the
document since the mapping is returned as well.
The downside of this approach is we wouldn't be able to ensure the same order
of keys in the JSON object. Currently the `jiffy` JSON encoder respects order
of keys.
```
4> jiffy:encode({[{bbb, 1}, {aaa, 12}]}).
<<"{\"bbb\":1,\"aaa\":12}">>
5> jiffy:encode({[{aaa, 12}, {bbb, 1}]}).
<<"{\"aaa\":12,\"bbb\":1}">>
```
Best regards,
iilyak
On 2019/01/30 13:02:57, Ilya Khlopotov <iil...@apache.org> wrote:
> As you might already know the FoundationDB has a number of limitations which
> influences the way we might store JSON documents. The limitations are:
>
> | limitation |recommended value|recommended max|absolute max|
> |-------------------------|----------------------:|--------------------:|--------------:|
> | transaction duration | |
> | 5 sec |
> | transaction data size | |
> | 10 Mb |
> | key size | 32 bytes | 1
> kB | 10 kB |
> | value size | |
> 10 kB | 100 kB |
>
> In order to fit the JSON document into 100kB we would have to partition it in
> some way. There are three ways of partitioning the document
> 1. store multiple binary blobs (parts) in different keys
> 2. flatten JSON structure and store every path leading to a scalar value
> under own key
> 3. measure the size of different branches of a tree representing the JSON
> document (while we parse) and use another key for the branch when we about to
> exceed the limit
>
> - The first approach is the simplest but it wouldn't allow us to access parts
> of the document.
> - The downsides of a second approach are:
> - flattened JSON structure would have long paths which means longer keys
> - the scalar value cannot be more than 100kb (unless we split it as well)
> - Third approach falls short in cases when the structure of the document
> doesn't allow a clean cut off branches:
> - complex rules to handle all corner cases
>
> The goals of this thread are:
> - to collect ideas on how to encode and store the JSON document
> - to comment on the collected ideas
>
> Non goals:
> - the storage of metadata for the document would be discussed elsewhere
> - thumb stones
> - edit conflicts
> - revisions
>
> Best regards,
> iilyak
>
