Fix #19856 - Set the db in mysql/mariadb for metric computations (#19994)

* use db for mysql/mariadb

* format

ingestion/src/metadata/mixins/sqalchemy/sqa_mixin.py

@@ -24,6 +24,12 @@ from metadata.generated.schema.entity.data.table import Table
 from metadata.generated.schema.entity.services.connections.database.databricksConnection import (
     DatabricksConnection,
 )
+from metadata.generated.schema.entity.services.connections.database.mariaDBConnection import (
+    MariaDBConnection,
+)
+from metadata.generated.schema.entity.services.connections.database.mysqlConnection import (
+    MysqlConnection,
+)
 from metadata.generated.schema.entity.services.connections.database.snowflakeConnection import (
     SnowflakeType,
 )
@@ -79,22 +85,27 @@ class SQAInterfaceMixin(Root):
             )
 
     def set_catalog(self, session) -> None:
-        """Set catalog for the session. Right now only databricks and unity catalog requires it
+        """Set the catalog or database for the session.
 
         Args:
             session (Session): sqa session object
         """
-        if not isinstance(
+        if isinstance(
             self.service_connection_config,
             (UnityCatalogConnection, DatabricksConnection),
         ):
-            return
+            session.get_bind().execute(
-        bind = session.get_bind()
-        bind.execute(
                 "USE CATALOG %(catalog)s;",
                 {"catalog": self.service_connection_config.catalog},
             ).first()
 
+        if isinstance(
+            self.service_connection_config, (MysqlConnection, MariaDBConnection)
+        ):
+            session.get_bind().execute(
+                f"USE {self.table_entity.databaseSchema.name};",
+            )
+
     def close(self):
         """close session"""
         self.session.close()

ingestion/src/metadata/profiler/interface/sqlalchemy/profiler_interface.py

@@ -297,7 +297,7 @@ class SQAProfilerInterface(ProfilerInterface, SQAInterfaceMixin):
             column: the column to compute the metrics against
             metrics: list of metrics to compute
         Returns:
-            dictionnary of results
+            dictionary of results
         """
 
         if not metrics:

ingestion/src/metadata/profiler/metrics/window/first_quartile.py

@@ -88,7 +88,7 @@ class FirstQuartile(StaticMetric, PercentilMixin):
             except MemoryError:
                 logger.error(
                     f"Unable to compute Median for {self.col.name} due to memory constraints."
-                    f"We recommend using a smaller sample size or partitionning."
+                    f"We recommend using a smaller sample size or partitioning."
                 )
                 return None
             # check if nan

ingestion/src/metadata/profiler/metrics/window/median.py

@@ -87,7 +87,7 @@ class Median(StaticMetric, PercentilMixin):
             except MemoryError:
                 logger.error(
                     f"Unable to compute Median for {self.col.name} due to memory constraints."
-                    f"We recommend using a smaller sample size or partitionning."
+                    f"We recommend using a smaller sample size or partitioning."
                 )
                 return None
             try:

ingestion/src/metadata/profiler/metrics/window/third_quartile.py

@@ -88,7 +88,7 @@ class ThirdQuartile(StaticMetric, PercentilMixin):
             except MemoryError:
                 logger.error(
                     f"Unable to compute Median for {self.col.name} due to memory constraints."
-                    f"We recommend using a smaller sample size or partitionning."
+                    f"We recommend using a smaller sample size or partitioning."
                 )
                 return None
             # check if nan

ingestion/src/metadata/sampler/sqlalchemy/azuresql/sampler.py

@@ -51,7 +51,9 @@ class AzureSQLSampler(SQASampler):
 
     def get_sample_query(self, *, column=None) -> Query:
         """get query for sample data"""
-        rnd = self._base_sample_query(column).cte(f"{self.get_sampler_table_name()}_rnd")
+        rnd = self._base_sample_query(column).cte(
+            f"{self.get_sampler_table_name()}_rnd"
+        )
         query = self.client.query(rnd)
         return query.cte(f"{self.get_sampler_table_name()}_sample")