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383 changes: 383 additions & 0 deletions dev/generate_srs_registry.py
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#!/usr/bin/env python3

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

"""
Generate the Spatial Reference System (SRS) registry for Apache Spark.

Downloads CRS definitions from the PROJ (Cartographic Projections and
Coordinate Transformations Library) GitHub repository and generates a CSV
file used by Spark's SpatialReferenceSystemCache on both the JVM and Python
sides.

PROJ is a C/C++ library (https://proj.org/) that maintains the authoritative
EPSG and ESRI CRS databases. This script extracts SRID metadata from PROJ's
SQL source files, which are plain-text INSERT statements parseable without
SQLite.

The script produces entries from the following PROJ SQL files:
- geodetic_crs.sql (EPSG geodetic CRS: geographic, geocentric, etc.)
- projected_crs.sql (EPSG projected CRS)
- compound_crs.sql (EPSG compound CRS)
- vertical_crs.sql (EPSG vertical CRS)
- engineering_crs.sql (EPSG engineering CRS)
- esri.sql (ESRI geodetic, projected, compound, vertical, engineering CRS)

Additionally, the following special entries are added:
- SRID 0 -> SRID:0 (Spark convention: Cartesian, no defined SRS)
- SRID 4267 -> OGC:CRS27 (OGC standardization of NAD27)
- SRID 4269 -> OGC:CRS83 (OGC standardization of NAD83)
- SRID 4326 -> OGC:CRS84 (OGC standardization of WGS 84)

Prerequisites:
Python 3.9+ (no third-party packages required)

Usage:
# Generate from default PROJ version:
python dev/generate_srs_registry.py

# Generate from a specific PROJ version:
python dev/generate_srs_registry.py --proj-version 9.7.1

# Verify the generated files:
wc -l sql/api/src/main/resources/org/apache/spark/sql/srs_registry.csv
wc -l python/pyspark/sql/srs_registry.csv

Upgrade workflow:
1. Change --proj-version to the new PROJ release tag
2. Run this script
3. Review the diff (git diff) to see which SRIDs were added/removed
4. Run the SRS-related tests to verify correctness
"""

import argparse
import csv
import os
import re
import ssl
import sys
import urllib.request

# Default PROJ version to download SQL files from.
DEFAULT_PROJ_VERSION = "9.7.1"

# URL template for raw SQL files from the PROJ GitHub repository.
PROJ_RAW_URL = "https://raw.githubusercontent.com/OSGeo/PROJ/{version}/data/sql/{filename}"

# PROJ SQL files to download. EPSG CRS definitions are spread across dedicated
# per-table files, while ESRI definitions are all in a single file.
PROJ_SQL_FILES = [
"geodetic_crs.sql",
"projected_crs.sql",
"compound_crs.sql",
"vertical_crs.sql",
"engineering_crs.sql",
"esri.sql",
]

# OGC special cases: these SRIDs are standardized under OGC rather than EPSG.
# The OGC string IDs override the EPSG ones for these SRIDs.
OGC_SPECIAL_CASES = {
4267: "OGC:CRS27", # NAD27
4269: "OGC:CRS83", # NAD83
4326: "OGC:CRS84", # WGS 84
}

# Output paths for the generated CSV, relative to the Spark repo root.
JAVA_RESOURCE_PATH = os.path.join(
"sql", "api", "src", "main", "resources", "org", "apache", "spark", "sql", "srs_registry.csv"
)
PYTHON_RESOURCE_PATH = os.path.join("python", "pyspark", "sql", "srs_registry.csv")


def download_sql(version, filename):
"""Download a SQL file from the PROJ GitHub repository at a pinned version tag."""
url = PROJ_RAW_URL.format(version=version, filename=filename)
print(f" Downloading {url}")
try:
ctx = ssl.create_default_context()
ctx.check_hostname = False
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why disable verify/check?

ctx.verify_mode = ssl.CERT_NONE
with urllib.request.urlopen(url, context=ctx) as response:
return response.read().decode("utf-8")
except urllib.error.HTTPError as e:
print(f"ERROR: Failed to download {url}: {e}", file=sys.stderr)
print(f"Check that PROJ version '{version}' exists as a GitHub tag.", file=sys.stderr)
sys.exit(1)


def parse_sql_values(values_str):
"""
Parse the comma-separated fields inside a SQL VALUES(...) clause.

Handles SQL-quoted strings (single quotes with '' escape for literal
apostrophes) and unquoted NULL / integer literals.

Returns a list of string values, with NULL represented as None.
"""
fields = []
i = 0
n = len(values_str)
while i < n:
if values_str[i] in (" ", "\t"):
i += 1
continue
if values_str[i] == "'":
# Quoted string: scan until closing quote ('' is an escaped quote).
i += 1
buf = []
while i < n:
if values_str[i] == "'" and i + 1 < n and values_str[i + 1] == "'":
buf.append("'")
i += 2
elif values_str[i] == "'":
i += 1
break
else:
buf.append(values_str[i])
i += 1
fields.append("".join(buf))
elif values_str[i : i + 4].upper() == "NULL":
fields.append(None)
i += 4
else:
# Unquoted literal (integer, etc.)
j = i
while j < n and values_str[j] not in (",", ")"):
j += 1
fields.append(values_str[i:j].strip())
i = j
# Skip comma separator.
while i < n and values_str[i] in (",", " ", "\t"):
if values_str[i] == ",":
i += 1
break
i += 1
return fields


def parse_geodetic_crs(sql_content):
"""
Parse geodetic_crs INSERT statements from SQL content.

The `type` field (position 4) determines whether the CRS is geographic:
'geographic 2D', 'geographic 3D' -> geographic
'geocentric', 'other' -> non-geographic

Returns a list of (srid, string_id, is_geographic) tuples,
excluding deprecated entries and entries with non-numeric codes.
"""
results = []
pattern = re.compile(r'INSERT INTO "geodetic_crs" VALUES\((.+)\);', re.IGNORECASE)
for line in sql_content.splitlines():
match = pattern.search(line)
if not match:
continue
fields = parse_sql_values(match.group(1))
auth_name = fields[0]
code = fields[1]
crs_type = fields[4]
try:
srid = int(code)
except (ValueError, TypeError):
continue
is_geographic = crs_type is not None and crs_type.startswith("geographic")
string_id = f"{auth_name}:{code}"
results.append((srid, string_id, is_geographic))
return results


def parse_simple_crs(sql_content, table_name):
"""
Parse INSERT statements for CRS tables that are always non-geographic.

Works for projected_crs, compound_crs, and vertical_crs tables.
Fields used: auth_name (0), code (1).

Returns a list of (srid, string_id, is_geographic=False) tuples.
"""
results = []
pattern = re.compile(rf'INSERT INTO "{table_name}" VALUES\((.+)\);', re.IGNORECASE)
for line in sql_content.splitlines():
match = pattern.search(line)
if not match:
continue
fields = parse_sql_values(match.group(1))
auth_name = fields[0]
code = fields[1]
try:
srid = int(code)
except (ValueError, TypeError):
continue
string_id = f"{auth_name}:{code}"
results.append((srid, string_id, False))
return results


def parse_all_crs_from_sql(sql_content):
"""
Parse all CRS types (geodetic, projected, compound, vertical) from a
single SQL file. Used for multi-table files like esri.sql.
"""
entries = []
entries.extend(parse_geodetic_crs(sql_content))
for table in ["projected_crs", "compound_crs", "vertical_crs", "engineering_crs"]:
entries.extend(parse_simple_crs(sql_content, table))
return entries


def write_csv(entries, proj_version, output_path):
"""Write SRS entries to a CSV file with a metadata header."""
os.makedirs(os.path.dirname(output_path), exist_ok=True)
with open(output_path, "w", newline="") as f:
f.write(
f"# Generated by dev/generate_srs_registry.py from PROJ {proj_version}\n"
f"# Source: https://github.com/OSGeo/PROJ/tree/{proj_version}/data/sql\n"
f"# Do not edit manually. Re-run the script to regenerate.\n"
)
writer = csv.writer(f)
writer.writerow(["srid", "string_id", "is_geographic"])
for srid, string_id, is_geographic in sorted(entries):
writer.writerow([srid, string_id, str(is_geographic).lower()])


def main():
parser = argparse.ArgumentParser(
description="Generate the SRS registry for Apache Spark from PROJ data."
)
parser.add_argument(
"--proj-version",
default=DEFAULT_PROJ_VERSION,
help=f"PROJ release tag to download from (default: {DEFAULT_PROJ_VERSION})",
)
parser.add_argument(
"--repo-root",
default=None,
help="Path to the Spark repository root (auto-detected if not set)",
)
args = parser.parse_args()

# Auto-detect repo root: this script lives in dev/ under the repo root.
if args.repo_root:
repo_root = args.repo_root
else:
repo_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))

print(f"Spark repo root: {repo_root}")
print(f"PROJ version: {args.proj_version}")
print()

# Download PROJ SQL files.
print("Downloading PROJ SQL files...")
sql_files = {}
for filename in PROJ_SQL_FILES:
sql_files[filename] = download_sql(args.proj_version, filename)
print()

# Parse CRS entries from EPSG-specific files.
print("Parsing CRS entries...")
all_entries = []

geodetic = parse_geodetic_crs(sql_files["geodetic_crs.sql"])
print(f" geodetic_crs.sql: {len(geodetic)} entries")
all_entries.extend(geodetic)

projected = parse_simple_crs(sql_files["projected_crs.sql"], "projected_crs")
print(f" projected_crs.sql: {len(projected)} entries")
all_entries.extend(projected)

compound = parse_simple_crs(sql_files["compound_crs.sql"], "compound_crs")
print(f" compound_crs.sql: {len(compound)} entries")
all_entries.extend(compound)

vertical = parse_simple_crs(sql_files["vertical_crs.sql"], "vertical_crs")
print(f" vertical_crs.sql: {len(vertical)} entries")
all_entries.extend(vertical)

engineering = parse_simple_crs(sql_files["engineering_crs.sql"], "engineering_crs")
print(f" engineering_crs.sql: {len(engineering)} entries")
all_entries.extend(engineering)

# Parse ESRI entries from the combined esri.sql file.
esri = parse_all_crs_from_sql(sql_files["esri.sql"])
print(f" esri.sql: {len(esri)} entries")
all_entries.extend(esri)

print()

# Deduplicate: keep the first occurrence of each SRID.
seen = set()
deduped = []
duplicates = 0
for entry in all_entries:
if entry[0] not in seen:
deduped.append(entry)
seen.add(entry[0])
else:
duplicates += 1
if duplicates:
print(f" Removed {duplicates} duplicate SRID(s)")
all_entries = deduped

# Add Spark-specific entry: SRID 0 (Cartesian, no defined SRS).
all_entries.append((0, "SRID:0", False))
Comment on lines +337 to +338
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I think it makes more sense to do this inside the SpatialReferenceSystemCache.java and geo_utils.py instead of here. I believe it is cleaner that the data generated by this script map completely to what we get from Proj.


# Apply OGC special case overrides: replace string IDs for standardized SRIDs.
ogc_applied = 0
for i, (srid, string_id, is_geographic) in enumerate(all_entries):
if srid in OGC_SPECIAL_CASES:
all_entries[i] = (srid, OGC_SPECIAL_CASES[srid], is_geographic)
ogc_applied += 1
print(f" Applied {ogc_applied} OGC special case override(s)")

# Count entries by authority.
authority_counts = {}
for _, string_id, _ in all_entries:
auth = string_id.split(":")[0]
authority_counts[auth] = authority_counts.get(auth, 0) + 1

n_geographic = sum(1 for _, _, g in all_entries if g)
n_nongeographic = len(all_entries) - n_geographic
print()
print(
f" Total: {len(all_entries)} entries "
f"({n_geographic} geographic, {n_nongeographic} non-geographic)"
)
print(" Breakdown by authority:")
for auth in sorted(authority_counts):
print(f" {auth}: {authority_counts[auth]}")
print()

# Write CSV to both Java and Python resource directories.
java_path = os.path.join(repo_root, JAVA_RESOURCE_PATH)
python_path = os.path.join(repo_root, PYTHON_RESOURCE_PATH)

print("Writing CSV files...")
write_csv(all_entries, args.proj_version, java_path)
print(f" {java_path}")
write_csv(all_entries, args.proj_version, python_path)
print(f" {python_path}")
print()

print("Done. Verify with:")
print(f" wc -l {JAVA_RESOURCE_PATH}")
print(f" git diff {JAVA_RESOURCE_PATH}")


if __name__ == "__main__":
main()
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