setting `--max-read-records 0` reads zero records

[cardi]

setting `--max-read-records 0` reads zero records

[domoritz]

Huh, strange. max_read_records should only be used for schema inference. See

json2parquet/src/main.rs

Line 141 in 27dfa6a

match arrow::json::reader::infer_json_schema(&mut buf_reader, opts.max_read_records) {

. Do you see a bug there? Could you try stepping through the code and also actually check what is in the parquet file?

[cardi]

Sure, let me take a look.

I don't have any experience with Rust, so it will be a bit while I try to get familiar.

[cardi]

[...] check what is in the parquet file?

$ cat generate_parquets.sh
#!/usr/bin/env bash

./json2parquet --max-read-records 0 foo.json foo-0.parquet
./json2parquet --max-read-records 1 foo.json foo-1.parquet
./json2parquet --max-read-records 2 foo.json foo-2.parquet
./json2parquet --max-read-records 3 foo.json foo-3.parquet
./json2parquet --max-read-records 4 foo.json foo-4.parquet
./json2parquet                      foo.json foo-5.parquet

read_parquet.py:

#!/usr/bin/env python3

import pandas as pd

for i in range(6):
  fn = "foo-" + str(i) + ".parquet"
  df = pd.read_parquet(fn)
  print(fn)
  print(df)
  print()

output:

$ ./read_parquet.py
foo-0.parquet
Empty DataFrame
Columns: []
Index: []

foo-1.parquet
     key1
0  value1
1    None
2    None
3    None
4    None

foo-2.parquet
     key1    key2
0  value1    None
1    None  value2
2    None    None
3    None    None
4    None    None

foo-3.parquet
     key1    key2    key3
0  value1    None    None
1    None  value2    None
2    None    None  value3
3    None    None    None
4    None    None    None

foo-4.parquet
     key1    key2    key3    key4
0  value1    None    None    None
1    None  value2    None    None
2    None    None  value3    None
3    None    None    None  value4
4    None    None    None    None

foo-5.parquet
     key1    key2    key3    key4    key5
0  value1    None    None    None    None
1    None  value2    None    None    None
2    None    None  value3    None    None
3    None    None    None  value4    None
4    None    None    None    None  value5

[cardi]

I did some digging into arrow::json::reader::infer_json_schema, and it seems like it needs to read some records to build a schema and does not build a generic schema of string types.

(It's possible that arrow has some way of building a generic schema of all Strings, but I'd expect that it would still have to read through the entire JSON file.)

definition for arrow::json::reader::infer_json_schema which calls arrow::json::reader::infer_json_schema_from_iterator—this might be where columns are coerced into Strings if they don't match certain types?

I've tested this with the following JSON file:

{"key1":"value1"}
{"key2":"value2"}
{"key3":"value3"}
{"key4":"value4"}
{"key5":"value5"}
{"key1":"value1"}
{"key1":"value1"}
{"key1":"value1"}
{"key1":"value1"}
{"key1":"value1"}
{"key1":"value1"}
{"key1":"value1"}
{"key1":"value1"}

and with --max-read-records 1, the resulting Parquet is:

      key1
0   value1
1     None
2     None
3     None
4     None
5   value1
6   value1
7   value1
8   value1
9   value1
10  value1
11  value1
12  value1

---

For context, my use case for json2parquet is part of a workflow to convert network packet capture (.pcap) files --> JSON --> Parquet.

The converted JSON doesn't seem to have a consistent schema that can be inferred, e.g.,

Error: General("Error inferring schema: Json error: Expected scalar or scalar array JSON type, found: Object({ [...]

(It's very possible that I'm asking json2parquet to do something outside of a reasonable scope—I might have better success with selecting a few fields to extract from pcaps --> csv --> Parquet, which I'll try next.)

[cardi]

Oops—I might not have answered your earlier question.

My read of the code is that the following snippet puts a schema into schema:

json2parquet/src/main.rs

Lines 141 to 150 in 27dfa6a

	match arrow::json::reader::infer_json_schema(&mut buf_reader, opts.max_read_records) {
	Ok(schema) => {
	input.seek(SeekFrom::Start(0))?;
	Ok(schema)
	}
	Err(error) => Err(ParquetError::General(format!(
	"Error inferring schema: {}",
	error
	))),
	}

schema is then used later to assist with the JSON reading:

json2parquet/src/main.rs

Lines 165 to 167 in 27dfa6a

	let schema_ref = Arc::new(schema);
	let builder = ReaderBuilder::new().with_schema(schema_ref);
	let reader = builder.build(input)?;

I think the issue is arrow::json::reader::infer_json_schema does not return a "generic" schema of String types if max_read_records is set to 0, but instead returns an empty schema (and the resultant Parquet file would be empty):

{
  "fields": []
}

This seems like the expected (if not documented) behavior for arrow::json::reader::infer_json_schema, so perhaps it's just the usage statement that needs to be updated. (But it would be great to be able to generate "generic" schema of sorts!)