Add indexes to execution model

rdl/alembic/versions/3834c837f5f2_add_indexes_to_execution_model.py

@@ -0,0 +1,34 @@
+"""add indexes to execution_model
+
+Revision ID: 3834c837f5f2
+Revises: bb0c5e8d05e2
+Create Date: 2019-11-26 08:42:13.575198
+
+"""
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = '3834c837f5f2'
+down_revision = 'bb0c5e8d05e2'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_index('execution_model__index_on_execution_id_model_name', 'execution_model', ['execution_id', 'model_name'], unique=True, schema='rdl')
+    op.create_index('execution_model__index_on_model_name_completed_on', 'execution_model', ['model_name', 'completed_on'], unique=False, schema='rdl')
+    op.create_index(op.f('ix_rdl_execution_model_completed_on'), 'execution_model', ['completed_on'], unique=False, schema='rdl')
+    op.create_index(op.f('ix_rdl_execution_model_status'), 'execution_model', ['status'], unique=False, schema='rdl')
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_index(op.f('ix_rdl_execution_model_status'), table_name='execution_model', schema='rdl')
+    op.drop_index(op.f('ix_rdl_execution_model_completed_on'), table_name='execution_model', schema='rdl')
+    op.drop_index('execution_model__index_on_model_name_completed_on', table_name='execution_model', schema='rdl')
+    op.drop_index('execution_model__index_on_execution_id_model_name', table_name='execution_model', schema='rdl')
+    # ### end Alembic commands ###

rdl/entities/execution_model_entity.py

@@ -1,102 +1,107 @@
-import uuid
-
-from sqlalchemy import (
-    Column,
-    DateTime,
-    Integer,
-    String,
-    Boolean,
-    BigInteger,
-    ForeignKey,
-)
-from sqlalchemy.sql import func
-from sqlalchemy.dialects.postgresql import UUID
-from sqlalchemy.inspection import inspect
-
-from rdl.entities import Base
-from rdl.entities import ExecutionEntity
-from rdl.shared import Constants
-
-
-class ExecutionModelEntity(Base):
-    __tablename__ = "execution_model"
-    __table_args__ = {"schema": Constants.DATA_PIPELINE_EXECUTION_SCHEMA_NAME}
-    execution_model_id = Column(
-        UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
-    )
-    created_on = Column(
-        DateTime(timezone=True), nullable=False, server_default=func.now()
-    )
-    updated_on = Column(
-        DateTime(timezone=True),
-        nullable=False,
-        server_default=func.now(),
-        onupdate=func.now(),
-    )
-    execution_id = Column(
-        UUID(as_uuid=True),
-        ForeignKey(
-            f"{Constants.DATA_PIPELINE_EXECUTION_SCHEMA_NAME}."
-            f"{inspect(ExecutionEntity).tables[0].name}."
-            f"{inspect(ExecutionEntity).primary_key[0].name}"
-        ),
-        nullable=False,
-    )
-    model_name = Column(String(250), nullable=False)
-    status = Column(
-        String(50),
-        nullable=False,
-        server_default=str(Constants.ExecutionModelStatus.STARTED),
-    )
-    last_sync_version = Column(BigInteger, nullable=False)
-    sync_version = Column(BigInteger, nullable=False)
-    is_full_refresh = Column(Boolean, nullable=False)
-    full_refresh_reason = Column(String(100), nullable=False)
-    started_on = Column(
-        DateTime(timezone=True), server_default=func.now(), nullable=False
-    )
-    completed_on = Column(DateTime(timezone=True), nullable=True)
-    execution_time_ms = Column(BigInteger, nullable=True)
-    rows_processed = Column(BigInteger, nullable=True)
-    batches_processed = Column(Integer, nullable=True)
-    model_checksum = Column(String(100), nullable=False)
-    failure_reason = Column(String(1000), nullable=True)
-
-    def __str__(self):
-        load_type = (
-            f"FULL ({self.full_refresh_reason})"
-            if self.is_full_refresh
-            else f"INCREMENTAL from version '{self.last_sync_version}' to '{self.sync_version}'"
-        )
-        execution_time_s = None
-        rows_per_second = None
-
-        if self.execution_time_ms:
-            execution_time_s = max(self.execution_time_ms // 1000, 1)
-
-            if self.rows_processed:
-                rows_per_second = self.rows_processed / execution_time_s
-
-        return (
-            "Model: {model}; "
-            "Load type: {load_type}; "
-            "Status: {status}; "
-            "Started on: {started}; "
-            "Completed on: {completed}; "
-            "Execution time: {exec_time}; "
-            "Batches processed: {batches}; "
-            "Rows processed: {rows}; "
-            "Average rows processed per second: {rows_per_second};".format(
-                model=self.model_name,
-                load_type=load_type,
-                status=self.status,
-                started=self.started_on.isoformat(),
-                completed=self.completed_on.isoformat() if self.completed_on else "n/a",
-                exec_time=f"{execution_time_s}s" if execution_time_s else "n/a",
-                batches=f"{self.batches_processed:,}"
-                if self.batches_processed
-                else "n/a",
-                rows=f"{self.rows_processed:,}" if self.rows_processed else "n/a",
-                rows_per_second=f"{rows_per_second:,.2f}" if rows_per_second else "n/a",
-            )
-        )
+import uuid
+
+from sqlalchemy import (
+    Column,
+    DateTime,
+    Integer,
+    String,
+    Boolean,
+    BigInteger,
+    ForeignKey,
+    Index,
+)
+from sqlalchemy.sql import func
+from sqlalchemy.dialects.postgresql import UUID
+from sqlalchemy.inspection import inspect
+
+from rdl.entities import Base
+from rdl.entities import ExecutionEntity
+from rdl.shared import Constants
+
+
+class ExecutionModelEntity(Base):
+    __tablename__ = "execution_model"
+    __table_args__ = {"schema": Constants.DATA_PIPELINE_EXECUTION_SCHEMA_NAME}
+    execution_model_id = Column(
+        UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
+    )
+    created_on = Column(
+        DateTime(timezone=True), nullable=False, server_default=func.now()
+    )
+    updated_on = Column(
+        DateTime(timezone=True),
+        nullable=False,
+        server_default=func.now(),
+        onupdate=func.now(),
+    )
+    execution_id = Column(
+        UUID(as_uuid=True),
+        ForeignKey(
+            f"{Constants.DATA_PIPELINE_EXECUTION_SCHEMA_NAME}."
+            f"{inspect(ExecutionEntity).tables[0].name}."
+            f"{inspect(ExecutionEntity).primary_key[0].name}"
+        ),
+        nullable=False,
+    )
+    model_name = Column(String(250), nullable=False)
+    status = Column(
+        String(50),
+        nullable=False,
+        server_default=str(Constants.ExecutionModelStatus.STARTED),
+        index=True
+    )
+    last_sync_version = Column(BigInteger, nullable=False)
+    sync_version = Column(BigInteger, nullable=False)
+    is_full_refresh = Column(Boolean, nullable=False)
+    full_refresh_reason = Column(String(100), nullable=False)
+    started_on = Column(
+        DateTime(timezone=True), server_default=func.now(), nullable=False
+    )
+    completed_on = Column(DateTime(timezone=True), nullable=True, index=True)
+    execution_time_ms = Column(BigInteger, nullable=True)
+    rows_processed = Column(BigInteger, nullable=True)
+    batches_processed = Column(Integer, nullable=True)
+    model_checksum = Column(String(100), nullable=False)
+    failure_reason = Column(String(1000), nullable=True)
+
+    index_on_execution_id_model_name = Index("execution_model__index_on_execution_id_model_name", execution_id, model_name, unique=True)
+    index_on_model_name_completed_on = Index("execution_model__index_on_model_name_completed_on", model_name, completed_on)
+
+    def __str__(self):
+        load_type = (
+            f"FULL ({self.full_refresh_reason})"
+            if self.is_full_refresh
+            else f"INCREMENTAL from version '{self.last_sync_version}' to '{self.sync_version}'"
+        )
+        execution_time_s = None
+        rows_per_second = None
+
+        if self.execution_time_ms:
+            execution_time_s = max(self.execution_time_ms // 1000, 1)
+
+            if self.rows_processed:
+                rows_per_second = self.rows_processed / execution_time_s
+
+        return (
+            "Model: {model}; "
+            "Load type: {load_type}; "
+            "Status: {status}; "
+            "Started on: {started}; "
+            "Completed on: {completed}; "
+            "Execution time: {exec_time}; "
+            "Batches processed: {batches}; "
+            "Rows processed: {rows}; "
+            "Average rows processed per second: {rows_per_second};".format(
+                model=self.model_name,
+                load_type=load_type,
+                status=self.status,
+                started=self.started_on.isoformat(),
+                completed=self.completed_on.isoformat() if self.completed_on else "n/a",
+                exec_time=f"{execution_time_s}s" if execution_time_s else "n/a",
+                batches=f"{self.batches_processed:,}"
+                if self.batches_processed
+                else "n/a",
+                rows=f"{self.rows_processed:,}" if self.rows_processed else "n/a",
+                rows_per_second=f"{rows_per_second:,.2f}" if rows_per_second else "n/a",
+            )
+        )