import celery from datetime import datetime import pandas as pd import logging import json import uuid import zlib from caravel import ( app, db, models, utils, dataframe, results_backend) from caravel.db_engine_specs import LimitMethod QueryStatus = models.QueryStatus celery_app = celery.Celery(config_source=app.config.get('CELERY_CONFIG')) def is_query_select(sql): return sql.upper().startswith('SELECT') def create_table_as(sql, table_name, schema=None, override=False): """Reformats the query into the create table as query. Works only for the single select SQL statements, in all other cases the sql query is not modified. :param sql: string, sql query that will be executed :param table_name: string, will contain the results of the query execution :param override, boolean, table table_name will be dropped if true :return: string, create table as query """ # TODO(bkyryliuk): enforce that all the columns have names. Presto requires it # for the CTA operation. # TODO(bkyryliuk): drop table if allowed, check the namespace and # the permissions. # TODO raise if multi-statement if schema: table_name = schema + '.' + table_name exec_sql = '' if is_query_select(sql): if override: exec_sql = 'DROP TABLE IF EXISTS {table_name};\n' exec_sql += "CREATE TABLE {table_name} AS \n{sql}" else: raise Exception("Could not generate CREATE TABLE statement") return exec_sql.format(**locals()) @celery_app.task def get_sql_results(query_id, return_results=True, store_results=False): """Executes the sql query returns the results.""" session = db.session() session.commit() # HACK query = session.query(models.Query).filter_by(id=query_id).one() database = query.database executed_sql = query.sql.strip().strip(';') db_engine_spec = database.db_engine_spec def handle_error(msg): """Local method handling error while processing the SQL""" query.error_message = msg query.status = QueryStatus.FAILED query.tmp_table_name = None session.commit() raise Exception(query.error_message) # Limit enforced only for retrieving the data, not for the CTA queries. is_select = is_query_select(executed_sql); if not is_select and not database.allow_dml: handle_error( "Only `SELECT` statements are allowed against this database") if query.select_as_cta: if not is_select: handle_error( "Only `SELECT` statements can be used with the CREATE TABLE " "feature.") if not query.tmp_table_name: start_dttm = datetime.fromtimestamp(query.start_time) query.tmp_table_name = 'tmp_{}_table_{}'.format( query.user_id, start_dttm.strftime('%Y_%m_%d_%H_%M_%S')) executed_sql = create_table_as( executed_sql, query.tmp_table_name, database.force_ctas_schema) query.select_as_cta_used = True elif ( query.limit and is_select and db_engine_spec.limit_method == LimitMethod.WRAP_SQL): executed_sql = database.wrap_sql_limit(executed_sql, query.limit) query.limit_used = True engine = database.get_sqla_engine(schema=query.schema) try: query.executed_sql = executed_sql logging.info("Running query: \n{}".format(executed_sql)) result_proxy = engine.execute(query.executed_sql, schema=query.schema) except Exception as e: logging.exception(e) handle_error(utils.error_msg_from_exception(e)) cursor = result_proxy.cursor query.status = QueryStatus.RUNNING session.flush() db_engine_spec.handle_cursor(cursor, query, session) cdf = None if result_proxy.cursor: column_names = [col[0] for col in result_proxy.cursor.description] if db_engine_spec.limit_method == LimitMethod.FETCH_MANY: data = result_proxy.fetchmany(query.limit) else: data = result_proxy.fetchall() cdf = dataframe.CaravelDataFrame( pd.DataFrame(data, columns=column_names)) query.rows = result_proxy.rowcount query.progress = 100 query.status = QueryStatus.SUCCESS if query.rows == -1 and cdf: # Presto doesn't provide result_proxy.row_count query.rows = cdf.size if query.select_as_cta: query.select_sql = '{}'.format(database.select_star( query.tmp_table_name, limit=query.limit)) query.end_time = utils.now_as_float() session.flush() payload = { 'query_id': query.id, 'status': query.status, 'data': [], } payload['data'] = cdf.data if cdf else [] payload['columns'] = cdf.columns_dict if cdf else [] payload['query'] = query.to_dict() payload = json.dumps(payload, default=utils.json_iso_dttm_ser) if store_results and results_backend: key = '{}'.format(uuid.uuid4()) logging.info("Storing results in results backend, key: {}".format(key)) results_backend.set(key, zlib.compress(payload)) query.results_key = key session.flush() session.commit() if return_results: return payload