Query Translation and SQL Lineage Parser Errors

SQL queries from data warehouse logs are failing to parse correctly, resulting in missing or incorrect lineage. This commonly occurs with complex SQL queries, non-standard SQL dialects, or unsupported SQL features.

Common Error Messages:

• SQL parsing failed for query
• Unable to extract table references
• Unsupported SQL syntax
• ParseException at line X

You Might Be Asking:

• Why isn't my SQL query parsing correctly?
• Which SQL dialects are supported?
• Can I improve SQL parsing accuracy?

1. Configure SQL parser in ingestion:

Example for Snowflake. This can be adapted for other data sources/connectors like BigQuery, Redshift, or other SQL-based platforms.

source:
  type: snowflake
  config:
    include_table_lineage: true

    # Choose SQL parser
    sql_parser: "sqlglot"  # Recommended (default)
    # Alternative: "sql-metadata" (faster, less comprehensive)

    # SQL parsing options
    sql_parser_config:
      use_external_process: true
      timeout_seconds: 30

2. Handle complex SQL patterns:

source:
  config:
    # For queries with CTEs, temp tables, etc.
    parse_queries_with_ctes: true

    # Handle dialect-specific features
    sql_dialect: "snowflake"  # or "bigquery", "postgres", etc.

    # Fallback for unparseable queries
    sql_parsing_fallback: "skip"  # or "log_warning"

3. Pre-process queries before parsing:

from datahub.utilities.sql_parser import SQLParser

def preprocess_query(sql):
    # Remove comments
    sql = re.sub(r'--.*?$', '', sql, flags=re.MULTILINE)
    sql = re.sub(r'/\*.*?\*/', '', sql, flags=re.DOTALL)

    # Normalize whitespace
    sql = ' '.join(sql.split())

    # Handle dialect-specific syntax
    sql = sql.replace('`', '"')  # BigQuery to standard

    return sql

# Use in custom ingestion
parser = SQLParser(preprocess_query(raw_sql))
tables = parser.get_tables()

4. Debug SQL parsing issues:

from datahub.utilities.sql_parser import SQLParser
import logging

# Enable debug logging
logging.basicConfig(level=logging.DEBUG)

# Test specific query
sql = """
    INSERT INTO target_table
    SELECT t1.*, t2.amount
    FROM source_table_1 t1
    JOIN source_table_2 t2 ON t1.id = t2.id
"""

try:
    parser = SQLParser(sql, dialect="snowflake")
    tables = parser.get_tables()
    print(f"Source tables: {tables}")
except Exception as e:
    print(f"Parsing failed: {e}")
    # Log the problematic query
    with open("failed_queries.log", "a") as f:
        f.write(f"\n\nFailed query:\n{sql}\nError: {e}\n")

5. Use manual lineage for unparseable queries:

Example for Snowflake. This can be adapted for other data sources/connectors.

# For queries that can't be parsed, emit manual lineage
from datahub.emitter.mce_builder import make_dataset_urn
from datahub.metadata.schema_classes import UpstreamLineageClass, UpstreamClass

# If SQL parsing fails, define lineage explicitly
upstream_lineage = UpstreamLineageClass(
    upstreams=[
        UpstreamClass(
            dataset=make_dataset_urn("snowflake", "db.schema.source1"),
            type="TRANSFORMED"
        ),
        UpstreamClass(
            dataset=make_dataset_urn("snowflake", "db.schema.source2"),
            type="TRANSFORMED"
        )
    ]
)

emitter.emit_mcp(
    entity_urn=make_dataset_urn("snowflake", "db.schema.target"),
    aspect_name="upstreamLineage",
    aspect=upstream_lineage
)

SQLglot parser handles most standard SQL and many dialect-specific features. For very complex queries or proprietary SQL extensions, consider using manual lineage. Log failed queries for analysis and parser improvement.

• SQL Parser
• Lineage Debugging