MS SQL MataData Extractor (#252)

* MS SQL MataData Extractor

* Fix Python 2.7 Build Failure

* Added MS SQL How To Use Guide

* Added MS SQL How To Use Guide

README.md

@@ -181,7 +181,7 @@ If using the filters option here is the input format
 #### [PostgresMetadataExtractor](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/extractor/postgres_metadata_extractor.py "PostgresMetadataExtractor")
 An extractor that extracts table and column metadata including database, schema, table name, table description, column name and column description from a Postgres or Redshift database.
 
-By default, the Postgres/Redshift database name is used as the cluter name. To override this, set `USE_CATALOG_AS_CLUSTER_NAME`
+By default, the Postgres/Redshift database name is used as the cluster name. To override this, set `USE_CATALOG_AS_CLUSTER_NAME`
 to `False`, and `CLUSTER_KEY` to what you wish to use as the cluster name.
 
 The `where_clause_suffix` below should define which schemas you'd like to query (see [the sample dag](https://github.com/lyft/amundsendatabuilder/blob/master/example/dags/postgres_sample_dag.py) for an example).
@@ -201,6 +201,30 @@ job = DefaultJob(
 job.launch()
 ```
 
+#### [MSSQLMetadataExtractor](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/extractor/mssql_metadata_extractor.py "PostgresMetadataExtractor")
+An extractor that extracts table and column metadata including database, schema, table name, table description, column name and column description from a Microsoft SQL database.
+
+By default, the Microsoft SQL Server Database name is used as the cluster name. To override this, set `USE_CATALOG_AS_CLUSTER_NAME`
+to `False`, and `CLUSTER_KEY` to what you wish to use as the cluster name.
+
+The `where_clause_suffix` below should define which schemas you'd like to query (`"('dbo','sys')"`).
+
+The SQL query driving the extraction is defined [here](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/extractor/mssql_metadata_extractor.py)
+
+This extractor is highly derived from [PostgresMetadataExtractor](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/extractor/postgres_metadata_extractor.py "PostgresMetadataExtractor"). 
+```python
+job_config = ConfigFactory.from_dict({
+	'extractor.mssql_metadata.{}'.format(MSSQLMetadataExtractor.WHERE_CLAUSE_SUFFIX_KEY): where_clause_suffix,
+    'extractor.mssql_metadata.{}'.format(MSSQLMetadataExtractor.USE_CATALOG_AS_CLUSTER_NAME): True,
+	'extractor.mssql_metadata.extractor.sqlalchemy.{}'.format(SQLAlchemyExtractor.CONN_STRING): connection_string()})
+job = DefaultJob(
+	conf=job_config,
+	task=DefaultTask(
+		extractor=MSSQLMetadataExtractor(),
+		loader=AnyLoader()))
+job.launch()
+```
+
 #### [MysqlMetadataExtractor](https://github.com/lyft/amundsendatabuilder/blob/master/databuilder/extractor/mysql_metadata_extractor.py "PostgresMetadataExtractor")
 An extractor that extracts table and column metadata including database, schema, table name, table description, column name and column description from a MYSQL database.
 

databuilder/extractor/mssql_metadata_extractor.py

+import logging
+import six
+from collections import namedtuple
+
+from pyhocon import ConfigFactory, ConfigTree  # noqa: F401
+from typing import Iterator, Union, Dict, Any  # noqa: F401
+
+from databuilder import Scoped
+from databuilder.extractor.base_extractor import Extractor
+from databuilder.extractor.sql_alchemy_extractor import SQLAlchemyExtractor
+from databuilder.models.table_metadata import TableMetadata, ColumnMetadata
+from itertools import groupby
+
+TableKey = namedtuple('TableKey', ['schema_name', 'table_name'])
+
+LOGGER = logging.getLogger(__name__)
+
+
+class MSSQLMetadataExtractor(Extractor):
+    """
+    Extracts Microsoft SQL Server table and column metadata from underlying
+    meta store database using SQLAlchemyExtractor
+    """
+
+    # SELECT statement from MS SQL to extract table and column metadata
+    SQL_STATEMENT = """
+            SELECT DISTINCT {cluster_source} AS CLUSTER,
+                 TBL.TABLE_SCHEMA AS [SCHEMA_NAME],
+                 TBL.TABLE_NAME AS [NAME],
+                 CAST(PROP.VALUE AS NVARCHAR(MAX)) AS [DESCRIPTION],
+                 COL.COLUMN_NAME AS [COL_NAME],
+                 COL.DATA_TYPE AS [COL_TYPE],
+                 CAST(PROP_COL.VALUE AS NVARCHAR(MAX)) AS [COL_DESCRIPTION],
+                 COL.ORDINAL_POSITION AS COL_SORT_ORDER
+FROM INFORMATION_SCHEMA.TABLES TBL
+INNER JOIN INFORMATION_SCHEMA.COLUMNS COL ON COL.TABLE_NAME = TBL.TABLE_NAME
+AND COL.TABLE_SCHEMA = TBL.TABLE_SCHEMA
+LEFT JOIN SYS.EXTENDED_PROPERTIES PROP ON PROP.MAJOR_ID = OBJECT_ID(TBL.TABLE_SCHEMA + '.' + TBL.TABLE_NAME)
+AND PROP.MINOR_ID = 0
+AND PROP.NAME = 'MS_Description'
+LEFT JOIN SYS.EXTENDED_PROPERTIES PROP_COL ON PROP_COL.MAJOR_ID = OBJECT_ID(TBL.TABLE_SCHEMA + '.' + TBL.TABLE_NAME)
+AND PROP_COL.MINOR_ID = COL.ORDINAL_POSITION
+AND PROP_COL.NAME = 'MS_Description'
+WHERE TBL.TABLE_TYPE = 'base table' {where_clause_suffix}
+ORDER BY CLUSTER,
+         SCHEMA_NAME,
+         NAME,
+         COL_SORT_ORDER;
+    """
+
+    # CONFIG KEYS
+    WHERE_CLAUSE_SUFFIX_KEY = 'where_clause_suffix'
+    CLUSTER_KEY = 'cluster_key'
+    USE_CATALOG_AS_CLUSTER_NAME = 'use_catalog_as_cluster_name'
+    DATABASE_KEY = 'database_key'
+
+    # Default values
+    DEFAULT_CLUSTER_NAME = 'DB_NAME()'
+
+    DEFAULT_CONFIG = ConfigFactory.from_dict(
+        {WHERE_CLAUSE_SUFFIX_KEY: '', CLUSTER_KEY: DEFAULT_CLUSTER_NAME, USE_CATALOG_AS_CLUSTER_NAME: True}
+    )
+
+    DEFAULT_WHERE_CLAUSE_VALUE = 'and tbl.table_schema in {schemas}'
+
+    def init(self, conf):
+        # type: (ConfigTree) -> None
+        conf = conf.with_fallback(MSSQLMetadataExtractor.DEFAULT_CONFIG)
+
+        self._cluster = '{}'.format(conf.get_string(MSSQLMetadataExtractor.CLUSTER_KEY))
+
+        if conf.get_bool(MSSQLMetadataExtractor.USE_CATALOG_AS_CLUSTER_NAME):
+            cluster_source = "DB_NAME()"
+        else:
+            cluster_source = "'{}'".format(self._cluster)
+
+        database = conf.get_string(MSSQLMetadataExtractor.DATABASE_KEY, default='mssql')
+        if six.PY2 and isinstance(database, six.text_type):
+            database = database.encode('utf-8', 'ignore')
+
+        self._database = database
+
+        config_where_clause = conf.get_string(MSSQLMetadataExtractor.WHERE_CLAUSE_SUFFIX_KEY)
+
+        logging.info("Crawling for Schemas %s", config_where_clause)
+
+        if len(config_where_clause) > 0:
+            where_clause_suffix = MSSQLMetadataExtractor.DEFAULT_WHERE_CLAUSE_VALUE.format(schemas=config_where_clause)
+        else:
+            where_clause_suffix = ''
+
+        self.sql_stmt = MSSQLMetadataExtractor.SQL_STATEMENT.format(
+            where_clause_suffix=where_clause_suffix,
+            cluster_source=cluster_source
+        )
+
+        LOGGER.info('SQL for MS SQL Metadata: {}'.format(self.sql_stmt))
+
+        self._alchemy_extractor = SQLAlchemyExtractor()
+        sql_alch_conf = Scoped.get_scoped_conf(conf, self._alchemy_extractor.get_scope()) \
+            .with_fallback(ConfigFactory.from_dict({SQLAlchemyExtractor.EXTRACT_SQL: self.sql_stmt}))
+
+        self._alchemy_extractor.init(sql_alch_conf)
+        self._extract_iter = None  # type: Union[None, Iterator]
+
+    def extract(self):
+        # type: () -> Union[TableMetadata, None]
+        if not self._extract_iter:
+            self._extract_iter = self._get_extract_iter()
+        try:
+            return next(self._extract_iter)
+        except StopIteration:
+            return None
+
+    def get_scope(self):
+        # type: () -> str
+        return 'extractor.mssql_metadata'
+
+    def _get_extract_iter(self):
+        # type: () -> Iterator[TableMetadata]
+        """
+        Using itertools.groupby and raw level iterator, it groups to table and yields TableMetadata
+        :return:
+        """
+        for key, group in groupby(self._get_raw_extract_iter(), self._get_table_key):
+            columns = []
+
+            for row in group:
+                last_row = row
+                columns.append(ColumnMetadata(row['col_name'], row['col_description'],
+                                              row['col_type'], row['col_sort_order']))
+
+            yield TableMetadata(self._database, last_row['cluster'],
+                                last_row['schema_name'],
+                                last_row['name'],
+                                last_row['description'],
+                                columns, tags=last_row['schema_name'])
+
+    def _get_raw_extract_iter(self):
+        # type: () -> Iterator[Dict[str, Any]]
+        """
+        Provides iterator of result row from SQLAlchemy extractor
+        :return:
+        """
+        row = self._alchemy_extractor.extract()
+        while row:
+            yield row
+            row = self._alchemy_extractor.extract()
+
+    def _get_table_key(self, row):
+        # type: (Dict[str, Any]) -> Union[TableKey, None]
+        """
+        Table key consists of schema and table name
+        :param row:
+        :return:
+        """
+        if row:
+            return TableKey(schema_name=row['schema_name'], table_name=row['name'])
+
+        return None