De-duplicated table info fetching code

discoverx/discovery.py

@@ -2,10 +2,10 @@
 
 from discoverx import logging
 from discoverx.msql import Msql
-from discoverx.scanner import TableInfo
+from discoverx.table_info import TableInfo
 from discoverx.scanner import Scanner, ScanResult
 from discoverx.rules import Rules, Rule
-from pyspark.sql import DataFrame, SparkSession
+from pyspark.sql import SparkSession
 
 logger = logging.Logging()
 

discoverx/explorer.py

@@ -2,108 +2,18 @@
 import copy
 import re
 from typing import Optional, List
-
 from discoverx import logging
 from discoverx.common import helper
 from discoverx.discovery import Discovery
 from discoverx.rules import Rule
-from discoverx.scanner import ColumnInfo, TableInfo
 from functools import reduce
 from pyspark.sql import DataFrame, SparkSession
 from pyspark.sql.functions import lit
-from pyspark.sql.types import Row
-
-logger = logging.Logging()
-
-
-class InfoFetcher:
-    def __init__(self, spark, columns_table_name="system.information_schema.columns") -> None:
-        self.columns_table_name = columns_table_name
-        self.spark = spark
-
-    def _to_info_list(self, info_rows: list[Row]) -> list[TableInfo]:
-        filtered_tables = [
-            TableInfo(
-                row["table_catalog"],
-                row["table_schema"],
-                row["table_name"],
-                [
-                    ColumnInfo(col["column_name"], col["data_type"], col["partition_index"], [])
-                    for col in row["table_columns"]
-                ],
-            )
-            for row in info_rows
-        ]
-        return filtered_tables
-
-    def get_tables_info(self, catalogs: str, schemas: str, tables: str, columns: list[str] = []) -> list[TableInfo]:
-        # Filter tables by matching filter
-        table_list_sql = self._get_table_list_sql(catalogs, schemas, tables, columns)
-
-        filtered_tables = self.spark.sql(table_list_sql).collect()
-
-        if len(filtered_tables) == 0:
-            raise ValueError(f"No tables found matching filter: {catalogs}.{schemas}.{tables}")
-
-        return self._to_info_list(filtered_tables)
-
-    def _get_table_list_sql(self, catalogs: str, schemas: str, tables: str, columns: list[str] = []) -> str:
-        """
-        Returns a SQL expression which returns a list of columns matching
-        the specified filters
-
-        Returns:
-            string: The SQL expression
-        """
-
-        if "*" in catalogs:
-            catalog_sql = f"""AND regexp_like(table_catalog, "^{catalogs.replace("*", ".*")}$")"""
-        else:
-            catalog_sql = f"""AND table_catalog = "{catalogs}" """
-
-        if "*" in schemas:
-            schema_sql = f"""AND regexp_like(table_schema, "^{schemas.replace("*", ".*")}$")"""
-        else:
-            schema_sql = f"""AND table_schema = "{schemas}" """
 
-        if "*" in tables:
-            table_sql = f"""AND regexp_like(table_name, "^{tables.replace("*", ".*")}$")"""
-        else:
-            table_sql = f"""AND table_name = "{tables}" """
-
-        if columns:
-            match_any_col = "|".join([f'({c.replace("*", ".*")})' for c in columns])
-            columns_sql = f"""AND regexp_like(column_name, "^{match_any_col}$")"""
-
-        sql = f"""
-        WITH tb_list AS (
-            SELECT DISTINCT
-                table_catalog, 
-                table_schema, 
-                table_name
-            FROM {self.columns_table_name}
-            WHERE 
-                table_schema != "information_schema" 
-                {catalog_sql if catalogs != "*" else ""}
-                {schema_sql if schemas != "*" else ""}
-                {table_sql if tables != "*" else ""}
-                {columns_sql if columns else ""}
-        )
+from discoverx.table_info import InfoFetcher, TableInfo
 
-        SELECT
-            info_schema.table_catalog, 
-            info_schema.table_schema, 
-            info_schema.table_name, 
-            collect_list(struct(column_name, data_type, partition_index)) as table_columns
-        FROM {self.columns_table_name} info_schema
-        INNER JOIN tb_list ON (
-            info_schema.table_catalog <=> tb_list.table_catalog AND
-            info_schema.table_schema = tb_list.table_schema AND
-            info_schema.table_name = tb_list.table_name)
-        GROUP BY info_schema.table_catalog, info_schema.table_schema, info_schema.table_name
-        """
 
-        return helper.strip_margin(sql)
+logger = logging.Logging()
 
 
 class DataExplorer:

discoverx/msql.py

@@ -2,7 +2,7 @@
 from dataclasses import dataclass
 from functools import reduce
 from discoverx import logging
-from discoverx.scanner import ColumnInfo, TableInfo
+from discoverx.table_info import ColumnInfo, TableInfo
 from discoverx.common.helper import strip_margin
 from fnmatch import fnmatch
 from pyspark.sql.functions import lit

discoverx/scanner.py

@@ -9,36 +9,12 @@
 
 from discoverx.common.helper import strip_margin, format_regex
 from discoverx import logging
+from discoverx.table_info import InfoFetcher, TableInfo
 from discoverx.rules import Rules, RuleTypes
 
 logger = logging.Logging()
 
 
-@dataclass
-class ColumnInfo:
-    name: str
-    data_type: str
-    partition_index: int
-    classes: list[str]
-
-
-@dataclass
-class TableInfo:
-    catalog: Optional[str]
-    schema: str
-    table: str
-    columns: list[ColumnInfo]
-
-    def get_columns_by_class(self, class_name: str):
-        return [ClassifiedColumn(col.name, class_name) for col in self.columns if class_name in col.classes]
-
-
-@dataclass
-class ClassifiedColumn:
-    name: str
-    class_name: str
-
-
 @dataclass
 class ScanContent:
     table_list: List[TableInfo]
@@ -181,59 +157,12 @@ def __init__(
         self.rule_list = self.rules.get_rules(rule_filter=self.rules_filter)
         self.scan_result: Optional[ScanResult] = None
 
-    def _get_list_of_tables(self) -> List[TableInfo]:
-        table_list_sql = self._get_table_list_sql()
-
-        rows = self.spark.sql(table_list_sql).collect()
-        filtered_tables = [
-            TableInfo(
-                row["table_catalog"],
-                row["table_schema"],
-                row["table_name"],
-                [
-                    ColumnInfo(col["column_name"], col["data_type"], col["partition_index"], [])
-                    for col in row["table_columns"]
-                ],
-            )
-            for row in rows
-        ]
-        return filtered_tables
-
-    def _get_table_list_sql(self):
-        """
-        Returns a SQL expression which returns a list of columns matching
-        the specified filters
-
-        Returns:
-            string: The SQL expression
-        """
-
-        catalog_sql = f"""AND regexp_like(table_catalog, "^{self.catalogs.replace("*", ".*")}$")"""
-        schema_sql = f"""AND regexp_like(table_schema, "^{self.schemas.replace("*", ".*")}$")"""
-        table_sql = f"""AND regexp_like(table_name, "^{self.tables.replace("*", ".*")}$")"""
-
-        sql = f"""
-        SELECT 
-            table_catalog, 
-            table_schema, 
-            table_name, 
-            collect_list(struct(column_name, data_type, partition_index)) as table_columns
-        FROM {self.columns_table_name}
-        WHERE 
-            table_schema != "information_schema" 
-            {catalog_sql if self.catalogs != "*" else ""}
-            {schema_sql if self.schemas != "*" else ""}
-            {table_sql if self.tables != "*" else ""}
-        GROUP BY table_catalog, table_schema, table_name
-        """
-
-        return strip_margin(sql)
-
     def _resolve_scan_content(self) -> ScanContent:
         if self.table_list:
             table_list = self.table_list
         else:
-            table_list = self._get_list_of_tables()
+            info_fetcher = InfoFetcher(self.spark, columns_table_name=self.columns_table_name)
+            table_list = info_fetcher.get_tables_info(self.catalogs, self.schemas, self.tables)
         catalogs = set(map(lambda x: x.catalog, table_list))
         schemas = set(map(lambda x: f"{x.catalog}.{x.schema}", table_list))
 

discoverx/table_info.py

@@ -0,0 +1,119 @@
+from typing import Optional
+from discoverx.common import helper
+from pyspark.sql.types import Row
+from dataclasses import dataclass
+
+
+@dataclass
+class ColumnInfo:
+    name: str
+    data_type: str
+    partition_index: int
+    classes: list[str]
+
+
+@dataclass
+class TableInfo:
+    catalog: Optional[str]
+    schema: str
+    table: str
+    columns: list[ColumnInfo]
+
+    def get_columns_by_class(self, class_name: str):
+        return [ClassifiedColumn(col.name, class_name) for col in self.columns if class_name in col.classes]
+
+
+@dataclass
+class ClassifiedColumn:
+    name: str
+    class_name: str
+
+
+class InfoFetcher:
+    def __init__(self, spark, columns_table_name="system.information_schema.columns") -> None:
+        self.columns_table_name = columns_table_name
+        self.spark = spark
+
+    def _to_info_list(self, info_rows: list[Row]) -> list[TableInfo]:
+        filtered_tables = [
+            TableInfo(
+                row["table_catalog"],
+                row["table_schema"],
+                row["table_name"],
+                [
+                    ColumnInfo(col["column_name"], col["data_type"], col["partition_index"], [])
+                    for col in row["table_columns"]
+                ],
+            )
+            for row in info_rows
+        ]
+        return filtered_tables
+
+    def get_tables_info(self, catalogs: str, schemas: str, tables: str, columns: list[str] = []) -> list[TableInfo]:
+        # Filter tables by matching filter
+        table_list_sql = self._get_table_list_sql(catalogs, schemas, tables, columns)
+
+        filtered_tables = self.spark.sql(table_list_sql).collect()
+
+        if len(filtered_tables) == 0:
+            raise ValueError(f"No tables found matching filter: {catalogs}.{schemas}.{tables}")
+
+        return self._to_info_list(filtered_tables)
+
+    def _get_table_list_sql(self, catalogs: str, schemas: str, tables: str, columns: list[str] = []) -> str:
+        """
+        Returns a SQL expression which returns a list of columns matching
+        the specified filters
+
+        Returns:
+            string: The SQL expression
+        """
+
+        if "*" in catalogs:
+            catalog_sql = f"""AND regexp_like(table_catalog, "^{catalogs.replace("*", ".*")}$")"""
+        else:
+            catalog_sql = f"""AND table_catalog = "{catalogs}" """
+
+        if "*" in schemas:
+            schema_sql = f"""AND regexp_like(table_schema, "^{schemas.replace("*", ".*")}$")"""
+        else:
+            schema_sql = f"""AND table_schema = "{schemas}" """
+
+        if "*" in tables:
+            table_sql = f"""AND regexp_like(table_name, "^{tables.replace("*", ".*")}$")"""
+        else:
+            table_sql = f"""AND table_name = "{tables}" """
+
+        if columns:
+            match_any_col = "|".join([f'({c.replace("*", ".*")})' for c in columns])
+            columns_sql = f"""AND regexp_like(column_name, "^{match_any_col}$")"""
+
+        sql = f"""
+        WITH tb_list AS (
+            SELECT DISTINCT
+                table_catalog, 
+                table_schema, 
+                table_name
+            FROM {self.columns_table_name}
+            WHERE 
+                table_schema != "information_schema" 
+                {catalog_sql if catalogs != "*" else ""}
+                {schema_sql if schemas != "*" else ""}
+                {table_sql if tables != "*" else ""}
+                {columns_sql if columns else ""}
+        )
+
+        SELECT
+            info_schema.table_catalog, 
+            info_schema.table_schema, 
+            info_schema.table_name, 
+            collect_list(struct(column_name, data_type, partition_index)) as table_columns
+        FROM {self.columns_table_name} info_schema
+        INNER JOIN tb_list ON (
+            info_schema.table_catalog <=> tb_list.table_catalog AND
+            info_schema.table_schema = tb_list.table_schema AND
+            info_schema.table_name = tb_list.table_name)
+        GROUP BY info_schema.table_catalog, info_schema.table_schema, info_schema.table_name
+        """
+
+        return helper.strip_margin(sql)

tests/unit/msql_test.py

@@ -4,7 +4,7 @@
 import pandas as pd
 import pytest
 from discoverx.common.helper import strip_margin
-from discoverx.scanner import ColumnInfo, TableInfo
+from discoverx.table_info import ColumnInfo, TableInfo
 from discoverx.msql import Msql, SQLRow
 from discoverx.scanner import ScanResult