Add support for deserializing list-encoded JSON structs [#6558]

[jagill]

Which issue does this PR close?

Closes #6558.

Rationale for this change

Currently, a StructArray can only be deserialized from a JSON object (e.g. {a: 1, b: "c"}), but some services (e.g. Presto and Trino) encode ROW types as JSON lists (e.g. [1, "c"]) because this is more compact, and the schema is known.
Arrow-json cannot currently deserialize these.

What changes are included in this PR?

This PR adds the ability to parse JSON lists into StructArrays, if the StructParseMode is set to ListOnly. In ListOnly mode, object-encoded structs raise an error. Setting to ObjectOnly (the default) has the original parsing behavior.

Are there any user-facing changes?

Users may set the StructParsingMode enum to ListOnly to parse list-style structs. The associated enum,
variants, and method have been documented. I'm happy to update any other documentation.

Discussion topics

1. I've made a JsonParseMode struct instead of a bool flag for two reasons. One is that it's self-descriptive (what would true be?), and the other is that it allows a future Mixed mode that could deserialize either. The latter isn't currently requested by anyone.
2. I kept the error messages as similar to the old messages as possible. I considered having more specific error messages (like "Encountered a '[' when parsing a Struct, but the StructParseMode is ObjectOnly" or similar), but wanted to hear opinions before I went that route.
3. I'm not attached to any name/code-style/etc, so happy to modify to fit local conventions.
4. One requirement was that benchmarks do not regress. My running of benchmarks have been inconclusive (see https://gist.github.com/jagill/6749248171a1f12fb7c653ff70c5ed42). There are often small regressions or improvements in the single-digit % range whenever I switch between master and this PR. I suspect they are statistical but I wanted to note these.

[tustvold]

Sorry this is on my list to look into, but I've struggled to find time to look into it yet... I appreciate your patience and restraint from repeatedly tagging me (unlike some people are wont to do).

[jagill]

Are there any changes I could make to this PR to make it easier to review?

[alamb]

Thank you for this contribution @jagill and i very much apologize for the delay in reviewing -- we are always looking for more help:

• Looking for help maintaining (reviewing PRs) in arrow/parquet/object_store #6418

TLDR thoughts:

1. Are you planning / willing to implement serializing support too (aka support in json_writer)? That would then allow us to verify that data can be round-tripped
2. I believe this PR slows down performance (notes below)

API

I've made a JsonParseMode struct instead of a bool flag for two reasons. One is that it's self-descriptive (what would true be?), and the other is that it allows a future Mixed mode that could deserialize either. The latter isn't currently requested by anyone.

I agree that a struct is nice for the reasons you mention

Errors

I kept the error messages as similar to the old messages as possible. I considered having more specific error messages (like "Encountered a '[' when parsing a Struct, but the StructParseMode is ObjectOnly" or similar), but wanted to hear opinions before I went that route.

I think improved error messages are always better, but we can do them as a follow on PR

I'm not attached to any name/code-style/etc, so happy to modify to fit local conventions.

💯

Performance

One requirement was that benchmarks do not regress. My running of benchmarks have been inconclusive (see https://gist.github.com/jagill/6749248171a1f12fb7c653ff70c5ed42). There are often small regressions or improvements in the single-digit % range whenever I switch between master and this PR. I suspect they are statistical but I wanted to note these.

I am not sure what benchmarks you ran -- I think the most relevant ones are in arrow/src/json_reader.rs

I ran them like cargo bench --bench json_reader

Here are three back to back runs I did on my test bench:

++ critcmp master json-struct-from-list
group                    json-struct-from-list                  master
-----                    ---------------------                  ------
large_bench_primitive    1.17      4.2±0.05ms        ? ?/sec    1.00      3.6±0.01ms        ? ?/sec
small_bench_list         1.03     14.5±0.05µs        ? ?/sec    1.00     14.1±0.17µs        ? ?/sec
small_bench_primitive    1.00      7.2±0.04µs        ? ?/sec    1.00      7.2±0.02µs        ? ?/sec

group                    json-struct-from-list                  master
-----                    ---------------------                  ------
large_bench_primitive    1.16      4.2±0.03ms        ? ?/sec    1.00      3.6±0.01ms        ? ?/sec
small_bench_list         1.03     14.5±0.05µs        ? ?/sec    1.00     14.0±0.13µs        ? ?/sec
small_bench_primitive    1.00      7.2±0.03µs        ? ?/sec    1.01      7.2±0.03µs        ? ?/sec

++ critcmp master json-struct-from-list
group                    json-struct-from-list                  master
-----                    ---------------------                  ------
large_bench_primitive    1.15      4.2±0.01ms        ? ?/sec    1.00      3.7±0.01ms        ? ?/sec
small_bench_list         1.00     14.4±0.10µs        ? ?/sec    1.00     14.4±0.08µs        ? ?/sec
small_bench_primitive    1.00      7.1±0.03µs        ? ?/sec    1.06      7.6±0.05µs        ? ?/sec
++ popd
~/datafusion-benchmarking

It shows a pretty consistent slowdown in large_bench_primitive -- I left some suggestions on how to improve this

Again, sorry for the delay in reviewing

[alamb]

Performance wise, this code now has another conditional in the hot loop (each row)

        for (row, p) in pos.iter().enumerate() {
         if self.struct_parse_mode { 
           ..
        }
      }

I suspect the code would be fast (and easier to understand / cleaner) if you hoisted the check, something like

         if self.struct_parse_mode { 
            for (row, p) in pos.iter().enumerate() {
             ..
            }
          else {
                   for (row, p) in pos.iter().enumerate() {
             ..
            }
      }

[alamb]

Do you have a link to documentation / prior art for this type of JSON encoding of structs? Maybe to trino / presto docs that describe it in more full detail that we can add to this doc?

[jagill]

Sadly, the documentation of the format of the returned data is a little lacking. They describe that the top-level row is a list with one entry per column (https://prestodb.io/docs/current/develop/client-protocol.html#important-queryresults-attributes, https://trino.io/docs/current/develop/client-protocol.html#important-queryresults-attributes), but do not specify how any structural elements are serialized (or non-structural things like Datetimes etc). If it helps, I could add this to the Presto documentation.

[jagill]

Ok, I've hoisted the conditional outside the loop. It also had the effect (as you predicted) that the gnarly match statement for the delimiters is a bit easier to understand.

1. Are you planning / willing to implement serializing support too (aka support in json_writer)? That would then allow us to verify that data can be round-tripped

I was not planning to, because there was no use-case requiring it. But I'm certainly willing to, both for symmetry and for round-tripping. Is that something you'd want in this PR, or a follow-up?

2. I believe this PR slows down performance (notes below)

When I check, I'm consistently seeing no difference between the main branch and either of the variants:

❯ critcmp main inner-conditional
group                    inner-conditional                      main
-----                    -----------------                      ----
large_bench_primitive    1.00      2.7±0.01ms        ? ?/sec    1.00      2.7±0.03ms        ? ?/sec
small_bench_list         1.01      8.4±0.09µs        ? ?/sec    1.00      8.2±0.06µs        ? ?/sec
small_bench_primitive    1.01      4.6±0.03µs        ? ?/sec    1.00      4.6±0.04µs        ? ?/sec

❯ critcmp main outer-conditional
group                    outer-conditional                      main
-----                    -----------------                      ----
large_bench_primitive    1.00      2.7±0.03ms        ? ?/sec    1.00      2.7±0.03ms        ? ?/sec
small_bench_list         1.00      8.3±0.11µs        ? ?/sec    1.00      8.2±0.06µs        ? ?/sec
small_bench_primitive    1.00      4.6±0.05µs        ? ?/sec    1.00      4.6±0.04µs        ? ?/sec

❯ critcmp inner-conditional outer-conditional
group                    outer-conditional                      inner-conditional
-----                    -----------------                      -----------------
large_bench_primitive    1.00      2.7±0.03ms        ? ?/sec    1.00      2.7±0.01ms        ? ?/sec
small_bench_list         1.00      8.3±0.11µs        ? ?/sec    1.01      8.4±0.09µs        ? ?/sec
small_bench_primitive    1.00      4.6±0.05µs        ? ?/sec    1.01      4.6±0.03µs        ? ?/sec

(btw, I didn't know about critcmp; thanks for the pointer!)

However, I'm not running in an isolated environment, so the differences I saw in the past seemed to be related to other processes. I'm running on a M2 Mac and haven't tried on with x86 or other architectures, and haven't been able to isolate from the helpful random processes that Macos spins up, so I'll trust your benchmarks.