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fix(parquet): handle nested data types correctly #20320

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Feb 5, 2025
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fix(parquet): handle nested data types correctly #20320

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224 changes: 207 additions & 17 deletions e2e_test/s3/fs_sink.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,12 @@
def gen_data(file_num, item_num_per_file):
assert item_num_per_file % 2 == 0, \
f'item_num_per_file should be even to ensure sum(mark) == 0: {item_num_per_file}'

struct_type = pa.struct([
('field1', pa.int32()),
('field2', pa.string())
])

return [
[{
'id': file_id * item_num_per_file + item_id,
Expand Down Expand Up @@ -44,6 +50,7 @@ def gen_data(file_num, item_num_per_file):
'test_timestamptz_ms': pa.scalar(datetime.now().timestamp() * 1000, type=pa.timestamp('ms', tz='+00:00')),
'test_timestamptz_us': pa.scalar(datetime.now().timestamp() * 1000000, type=pa.timestamp('us', tz='+00:00')),
'test_timestamptz_ns': pa.scalar(datetime.now().timestamp() * 1000000000, type=pa.timestamp('ns', tz='+00:00')),
'nested_struct': pa.scalar((item_id, f'struct_value_{item_id}'), type=struct_type),
} for item_id in range(item_num_per_file)]
for file_id in range(file_num)
]
Expand All @@ -62,6 +69,50 @@ def do_test(config, file_num, item_num_per_file, prefix):
def _table():
return 's3_test_parquet'

print("test table function file scan")
cur.execute(f'''
SELECT
id,
name,
sex,
mark,
test_int,
test_int8,
test_uint8,
test_uint16,
test_uint32,
test_uint64,
test_float_16,
test_real,
test_double_precision,
test_varchar,
test_bytea,
test_date,
test_time,
test_timestamp_s,
test_timestamp_ms,
test_timestamp_us,
test_timestamp_ns,
test_timestamptz_s,
test_timestamptz_ms,
test_timestamptz_us,
test_timestamptz_ns,
nested_struct
FROM file_scan(
'parquet',
's3',
'http://127.0.0.1:9301',
'hummockadmin',
'hummockadmin',
's3://hummock001/test_file_scan/test_file_scan.parquet'
);''')
try:
result = cur.fetchone()
assert result[0] == 0, f'file scan assertion failed: the first column is {result[0]}, expect 0.'
except ValueError as e:
print(f"cur.fetchone() got ValueError: {e}")

print("file scan test pass")
# Execute a SELECT statement
cur.execute(f'''CREATE TABLE {_table()}(
id bigint primary key,
Expand All @@ -88,8 +139,8 @@ def _table():
test_timestamptz_s timestamptz,
test_timestamptz_ms timestamptz,
test_timestamptz_us timestamptz,
test_timestamptz_ns timestamptz

test_timestamptz_ns timestamptz,
nested_struct STRUCT<"field1" int, "field2" varchar>
) WITH (
connector = 's3',
match_pattern = '*.parquet',
Expand Down Expand Up @@ -169,7 +220,8 @@ def _table():
test_timestamptz_s,
test_timestamptz_ms,
test_timestamptz_us,
test_timestamptz_ns
test_timestamptz_ns,
nested_struct
from {_table()} WITH (
connector = 's3',
match_pattern = '*.parquet',
Expand All @@ -179,15 +231,14 @@ def _table():
s3.credentials.secret = 'hummockadmin',
s3.endpoint_url = 'http://hummock001.127.0.0.1:9301',
s3.path = 'test_parquet_sink/',
s3.file_type = 'parquet',
type = 'append-only',
force_append_only='true'
) FORMAT PLAIN ENCODE PARQUET(force_append_only='true');''')

print('Sink into s3 in parquet encode...')
# Execute a SELECT statement
cur.execute(f'''CREATE TABLE test_parquet_sink_table(
id bigint primary key,\
id bigint primary key,
name TEXT,
sex bigint,
mark bigint,
Expand All @@ -211,7 +262,8 @@ def _table():
test_timestamptz_s timestamptz,
test_timestamptz_ms timestamptz,
test_timestamptz_us timestamptz,
test_timestamptz_ns timestamptz
test_timestamptz_ns timestamptz,
nested_struct STRUCT<"field1" int, "field2" varchar>,
) WITH (
connector = 's3',
match_pattern = 'test_parquet_sink/*.parquet',
Expand All @@ -220,8 +272,8 @@ def _table():
s3.credentials.access = 'hummockadmin',
s3.credentials.secret = 'hummockadmin',
s3.endpoint_url = 'http://hummock001.127.0.0.1:9301',
refresh.interval.sec = 1,
) FORMAT PLAIN ENCODE PARQUET;''')

total_rows = file_num * item_num_per_file
MAX_RETRIES = 40
for retry_no in range(MAX_RETRIES):
Expand Down Expand Up @@ -262,19 +314,20 @@ def _table():
test_timestamptz_s,
test_timestamptz_ms,
test_timestamptz_us,
test_timestamptz_ns
test_timestamptz_ns,
nested_struct
from {_table()} WITH (
connector = 's3',
connector = 'snowflake',
match_pattern = '*.parquet',
s3.region_name = 'custom',
s3.bucket_name = 'hummock001',
s3.credentials.access = 'hummockadmin',
s3.credentials.secret = 'hummockadmin',
snowflake.aws_region = 'custom',
snowflake.s3_bucket = 'hummock001',
snowflake.aws_access_key_id = 'hummockadmin',
snowflake.aws_secret_access_key = 'hummockadmin',
s3.endpoint_url = 'http://hummock001.127.0.0.1:9301',
s3.path = 'test_json_sink/',
s3.file_type = 'json',
type = 'append-only',
force_append_only='true'
force_append_only='true',
refresh.interval.sec = 1,
) FORMAT PLAIN ENCODE JSON(force_append_only='true');''')

print('Sink into s3 in json encode...')
Expand Down Expand Up @@ -304,7 +357,8 @@ def _table():
test_timestamptz_s timestamptz,
test_timestamptz_ms timestamptz,
test_timestamptz_us timestamptz,
test_timestamptz_ns timestamptz
test_timestamptz_ns timestamptz,
nested_struct STRUCT<"field1" int, "field2" varchar>
) WITH (
connector = 's3',
match_pattern = 'test_json_sink/*.json',
Expand Down Expand Up @@ -343,8 +397,127 @@ def _assert_eq(field, got, expect):
cur.execute(f'drop table test_parquet_sink_table')
cur.execute(f'drop sink test_file_sink_json')
cur.execute(f'drop table test_json_sink_table')
cur.execute(f'drop table s3_test_parquet')
cur.close()
conn.close()

def test_file_sink_batching():
conn = psycopg2.connect(
host="localhost",
port="4566",
user="root",
database="dev"
)

# Open a cursor to execute SQL statements
cur = conn.cursor()


# Execute a SELECT statement
cur.execute(f'''CREATE TABLE t (v1 int, v2 int);''')

print('test file sink batching...\n')
cur.execute(f'''CREATE sink test_file_sink_batching as select
v1, v2 from t WITH (
connector = 's3',
s3.region_name = 'custom',
s3.bucket_name = 'hummock001',
s3.credentials.access = 'hummockadmin',
s3.credentials.secret = 'hummockadmin',
s3.endpoint_url = 'http://hummock001.127.0.0.1:9301',
s3.path = 'test_file_sink_batching/',
type = 'append-only',
rollover_seconds = 5,
max_row_count = 5,
force_append_only='true'
) FORMAT PLAIN ENCODE PARQUET(force_append_only='true');''')

cur.execute(f'''CREATE TABLE test_file_sink_batching_table(
v1 int,
v2 int,
) WITH (
connector = 's3',
match_pattern = 'test_file_sink_batching/*.parquet',
refresh.interval.sec = 1,
s3.region_name = 'custom',
s3.bucket_name = 'hummock001',
s3.credentials.access = 'hummockadmin',
s3.credentials.secret = 'hummockadmin',
s3.endpoint_url = 'http://hummock001.127.0.0.1:9301',
) FORMAT PLAIN ENCODE PARQUET;''')

cur.execute(f'''ALTER SINK test_file_sink_batching SET PARALLELISM = 2;''')

cur.execute(f'''INSERT INTO t VALUES (10, 10);''')


cur.execute(f'select count(*) from test_file_sink_batching_table')
# no item will be selectedpsq
result = cur.fetchone()

def _assert_eq(field, got, expect):
assert got == expect, f'{field} assertion failed: got {got}, expect {expect}.'
def _assert_greater(field, got, expect):
assert got > expect, f'{field} assertion failed: got {got}, expect {expect}.'

_assert_eq('count(*)', result[0], 0)
print('the rollover_seconds has not reached, count(*) = 0')


time.sleep(11)

cur.execute(f'select count(*) from test_file_sink_batching_table')
result = cur.fetchone()
_assert_eq('count(*)', result[0], 1)
print('the rollover_seconds has reached, count(*) = ', result[0])

cur.execute(f'''
INSERT INTO t VALUES (20, 20);
INSERT INTO t VALUES (30, 30);
INSERT INTO t VALUES (40, 40);
INSERT INTO t VALUES (50, 10);
''')

cur.execute(f'select count(*) from test_file_sink_batching_table')
# count(*) = 1
result = cur.fetchone()
_assert_eq('count(*)', result[0], 1)
print('the max row count has not reached, count(*) = ', result[0])

cur.execute(f'''
INSERT INTO t VALUES (60, 20);
INSERT INTO t VALUES (70, 30);
INSERT INTO t VALUES (80, 10);
INSERT INTO t VALUES (90, 20);
INSERT INTO t VALUES (100, 30);
INSERT INTO t VALUES (100, 10);
''')

time.sleep(10)

cur.execute(f'select count(*) from test_file_sink_batching_table')
result = cur.fetchone()
_assert_greater('count(*)', result[0], 1)
print('the rollover_seconds has reached, count(*) = ', result[0])

cur.execute(f'drop sink test_file_sink_batching;')
cur.execute(f'drop table t;')
cur.execute(f'drop table test_file_sink_batching_table;')
cur.close()
conn.close()
# delete objects

client = Minio(
"127.0.0.1:9301",
"hummockadmin",
"hummockadmin",
secure=False,
)
objects = client.list_objects("hummock001", prefix="test_file_sink_batching/", recursive=True)

for obj in objects:
client.remove_object("hummock001", obj.object_name)
print(f"Deleted: {obj.object_name}")



Expand Down Expand Up @@ -374,6 +547,21 @@ def _assert_eq(field, got, expect):
_s3(idx),
_local(idx)
)
# put parquet file to test table function file scan
if data:
first_file_data = data[0]
first_table = pa.Table.from_pandas(pd.DataFrame(first_file_data))

first_file_name = f"test_file_scan.parquet"
first_file_path = f"test_file_scan/{first_file_name}"

pq.write_table(first_table, "data_0.parquet")

client.fput_object(
"hummock001",
first_file_path,
"data_0.parquet"
)

# do test
do_test(config, FILE_NUM, ITEM_NUM_PER_FILE, run_id)
Expand All @@ -384,7 +572,9 @@ def _assert_eq(field, got, expect):

do_sink(config, FILE_NUM, ITEM_NUM_PER_FILE, run_id)

# clean up s3 files
# clean up s3 files
for idx, _ in enumerate(data):
client.remove_object("hummock001", _s3(idx))

# test file sink batching
test_file_sink_batching()
5 changes: 5 additions & 0 deletions src/connector/src/parser/parquet_parser.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ use risingwave_common::util::tokio_util::compat::FuturesAsyncReadCompatExt;
use crate::parser::ConnectorResult;
use crate::source::filesystem::opendal_source::opendal_enumerator::OpendalEnumerator;
use crate::source::filesystem::opendal_source::{OpendalGcs, OpendalPosixFs, OpendalS3};
use crate::source::iceberg::is_parquet_schema_match_source_schema;
use crate::source::reader::desc::SourceDesc;
use crate::source::{ConnectorProperties, SourceColumnDesc};
/// `ParquetParser` is responsible for converting the incoming `record_batch_stream`
Expand Down Expand Up @@ -110,6 +111,10 @@ impl ParquetParser {

if let Some(parquet_column) =
record_batch.column_by_name(rw_column_name)
&& is_parquet_schema_match_source_schema(
parquet_column.data_type(),
rw_data_type,
)
{
let arrow_field = IcebergArrowConvert
.to_arrow_field(rw_column_name, rw_data_type)?;
Expand Down
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