[dasksql] Adding SELECT and CREATE model examples
"auto_load_only": false,
"data": {
"query": {
- "query": "\nSHOW TOPICS\n;\n\n\nCREATE STREAM user_behavior (\n user_id BIGINT,\n item_id BIGINT,\n category_id BIGINT,\n behavior STRING,\n ts STRING\n) WITH (kafka_topic='user_behavior', value_format='json', partitions=1)\n;\n\n\nSELECT *\nFROM user_behavior\nEMIT CHANGES\nLIMIT 30\n;\n\n\nINSERT INTO user_behavior (\n user_id ,\n item_id ,\n category_id ,\n behavior ,\n ts\n)\nVALUES\n(1, 10, 20, 'buy', '1602998392')\n;\n",
+ "query": "\nSHOW TOPICS\n;\n\n\nCREATE STREAM user_behavior (\n user_id BIGINT,\n item_id BIGINT,\n category_id BIGINT,\n behavior STRING,\n ts STRING\n) WITH (kafka_topic='user_behavior', value_format='json', partitions=1)\n;\n\n\nSELECT *\nFROM user_behavior\nEMIT CHANGES\nLIMIT 5\n;\n\n\nINSERT INTO user_behavior (\n user_id ,\n item_id ,\n category_id ,\n behavior ,\n ts\n)\nVALUES\n(1, 10, 20, 'buy', '1602998392')\n;\n",
"type": 0,
"email_notify": false,
"is_parameterized": false,
"auto_load_only": false,
"data": {
"query": {
- "query": "\nSELECT\n FLOOR(trip_distance / 5) * 5 AS \"distance\",\n AVG(tip_amount) AS \"given tip\",\n AVG(predict_price(total_amount, trip_distance, passenger_count)) AS \"predicted tip\"\nFROM \"nyc-taxi\"\nWHERE\n trip_distance > 0 AND trip_distance < 50\nGROUP BY\n FLOOR(trip_distance / 5) * 5\n;\n",
+ "query": "\nSELECT *\nFROM \"schema\".\"nyc-taxi\"\nLIMIT 100\n;\n\nSELECT\n FLOOR(trip_distance / 5) * 5 AS \"distance\",\n AVG(tip_amount) AS \"given tip\",\n AVG(predict_price(total_amount, trip_distance, passenger_count)) AS \"predicted tip\"\nFROM \"nyc-taxi\"\nWHERE\n trip_distance > 0 AND trip_distance < 50\nGROUP BY\n FLOOR(trip_distance / 5) * 5\n;\n\nCREATE MODEL fare_estimator WITH (\n model_class = 'sklearn.ensemble.GradientBoostingClassifier',\n wrap_predict = True,\n target_column = 'fare_amount'\n) AS (\n SELECT trip_distance, fare_amount\n FROM \"nyc-taxi\"\n LIMIT 100\n)\n;\n",
"type": 0,
"email_notify": false,
"is_parameterized": false,
