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https://github.com/csunny/DB-GPT.git
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feat:update params
This commit is contained in:
aries_ckt
123
pilot/connections/conn_spark.py
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123
pilot/connections/conn_spark.py
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@@ -0,0 +1,123 @@
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from typing import Optional, Any
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from pyspark.sql import SparkSession, DataFrame
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from sqlalchemy import text
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from pilot.connections.base import BaseConnect
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class SparkConnect(BaseConnect):
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"""Spark Connect
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Args:
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Usage:
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"""
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"""db type"""
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db_type: str = "spark"
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"""db driver"""
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driver: str = "spark"
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"""db dialect"""
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dialect: str = "sparksql"
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def __init__(
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self,
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file_path: str,
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spark_session: Optional[SparkSession] = None,
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engine_args: Optional[dict]= None,
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**kwargs: Any
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) -> None:
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"""Initialize the Spark DataFrame from Datasource path
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return: Spark DataFrame
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"""
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self.spark_session = (
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spark_session or SparkSession.builder.appName("dbgpt").getOrCreate()
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)
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self.path = file_path
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self.table_name = "temp"
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self.df = self.create_df(self.path)
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@classmethod
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def from_file_path(
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cls, file_path: str, engine_args: Optional[dict] = None, **kwargs: Any
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):
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try:
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return cls(file_path=file_path, engine_args=engine_args)
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except Exception as e:
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print("load spark datasource error" + str(e))
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def create_df(self, path) -> DataFrame:
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"""Create a Spark DataFrame from Datasource path
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return: Spark DataFrame
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"""
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return self.spark_session.read.option("header", "true").csv(path)
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def run(self, sql):
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# self.log(f"llm ingestion sql query is :\n{sql}")
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# self.df = self.create_df(self.path)
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self.df.createOrReplaceTempView(self.table_name)
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df = self.spark_session.sql(sql)
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first_row = df.first()
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rows = [first_row.asDict().keys()]
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for row in df.collect():
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rows.append(row)
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return rows
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def query_ex(self, sql):
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rows = self.run(sql)
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field_names = rows[0]
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return field_names, rows
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def get_indexes(self, table_name):
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"""Get table indexes about specified table."""
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return ""
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def get_show_create_table(self, table_name):
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"""Get table show create table about specified table."""
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return "ans"
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def get_fields(self):
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"""Get column meta about dataframe."""
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return ",".join([f"({name}: {dtype})" for name, dtype in self.df.dtypes])
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def get_users(self):
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return []
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def get_grants(self):
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return []
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def get_collation(self):
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"""Get collation."""
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return "UTF-8"
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def get_charset(self):
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return "UTF-8"
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def get_db_list(self):
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return ["default"]
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def get_db_names(self):
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return ["default"]
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def get_database_list(self):
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return []
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def get_database_names(self):
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return []
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def table_simple_info(self):
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return f"{self.table_name}{self.get_fields()}"
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def get_table_comments(self, db_name):
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session = self._db_sessions()
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cursor = session.execute(
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text(
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f"""SELECT table, comment FROM system.tables WHERE database = '{db_name}'""".format(
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db_name
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)
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)
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)
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table_comments = cursor.fetchall()
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return [
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(table_comment[0], table_comment[1]) for table_comment in table_comments
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]
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@@ -1,132 +0,0 @@
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import re
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from typing import Optional, Any
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from sqlalchemy import text
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from pyspark.sql import SparkSession, DataFrame
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class SparkConnect:
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"""Connect Spark
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Args:
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Usage:
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"""
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"""db type"""
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# db_type: str = "spark"
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"""db driver"""
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driver: str = "spark"
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"""db dialect"""
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# db_dialect: str = "spark"
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def __init__(
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self,
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spark_session: Optional[SparkSession] = None,
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) -> None:
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self.spark_session = spark_session or SparkSession.builder.appName("dbgpt").master("local[*]").config("spark.sql.catalogImplementation", "hive").getOrCreate()
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def create_df(self, path)-> DataFrame:
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"""load path into spark"""
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path = "/Users/chenketing/Downloads/Warehouse_and_Retail_Sales.csv"
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return self.spark_session.read.csv(path)
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def run(self, sql):
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self.spark_session.sql(sql)
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return sql.show()
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def get_indexes(self, table_name):
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"""Get table indexes about specified table."""
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return ""
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def get_show_create_table(self, table_name):
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"""Get table show create table about specified table."""
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session = self._db_sessions()
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cursor = session.execute(text(f"SHOW CREATE TABLE {table_name}"))
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ans = cursor.fetchall()
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ans = ans[0][0]
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ans = re.sub(r"\s*ENGINE\s*=\s*MergeTree\s*", " ", ans, flags=re.IGNORECASE)
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ans = re.sub(
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r"\s*DEFAULT\s*CHARSET\s*=\s*\w+\s*", " ", ans, flags=re.IGNORECASE
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)
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ans = re.sub(r"\s*SETTINGS\s*\s*\w+\s*", " ", ans, flags=re.IGNORECASE)
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return ans
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def get_fields(self, df: DataFrame):
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"""Get column fields about specified table."""
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return "\n".join([f"{name}: {dtype}" for name, dtype in df.dtypes])
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def get_users(self):
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return []
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def get_grants(self):
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return []
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def get_collation(self):
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"""Get collation."""
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return "UTF-8"
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def get_charset(self):
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return "UTF-8"
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def get_database_list(self):
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return []
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def get_database_names(self):
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return []
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def get_table_comments(self, db_name):
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session = self._db_sessions()
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cursor = session.execute(
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text(
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f"""SELECT table, comment FROM system.tables WHERE database = '{db_name}'""".format(
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db_name
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)
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)
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)
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table_comments = cursor.fetchall()
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return [
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(table_comment[0], table_comment[1]) for table_comment in table_comments
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]
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if __name__ == "__main__":
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# spark = SparkSession.builder \
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# .appName("Spark-SQL and sqlalchemy") \
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# .getOrCreate()
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db_url = "spark://B-V0ECMD6R-0244.local:7077"
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# engine = create_engine(db_url)
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# engine = create_engine("sparksql:///?Server=127.0.0.1")
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# sqlContext = SQLContext(spark)
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# df = sqlContext.read.format("jdbc").option("url", db_url).option("dbtable",
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# "person").option(
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# "user", "username").option("password", "password").load()
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spark = (
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SparkSession.builder.appName("ckt")
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.master("local[*]")
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# .config("hive.metastore.uris", "thrift://localhost:9083")
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# .config("spark.sql.warehouse.dir", "/Users/chenketing/myhive/")
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.config("spark.sql.catalogImplementation", "hive")
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.enableHiveSupport()
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.getOrCreate()
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)
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# sqlContext.read.jdbc(url='jdbc:hive2://127.0.0.1:10000/default', table='pokes', properties=connProps)
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# df = spark.read.format("jdbc").option("url", "jdbc:hive2://localhost:10000/dbgpt_test").option("dbtable", "dbgpt_test.dbgpt_table").option("driver", "org.apache.hive.jdbc.HiveDriver").load()
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path = "/Users/chenketing/Downloads/Warehouse_and_Retail_Sales.csv"
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df = spark.read.csv(path)
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df.createOrReplaceTempView("warehouse1")
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# df = spark.sql("show databases")
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# spark.sql("CREATE TABLE IF NOT EXISTS default.db_test (id INT, name STRING)")
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# df = spark.sql("DESC default.db_test")
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# spark.sql("INSERT INTO default.db_test VALUES (1, 'Alice')")
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# spark.sql("INSERT INTO default.db_test VALUES (2, 'Bob')")
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# spark.sql("INSERT INTO default.db_test VALUES (3, 'Charlie')")
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# df = spark.sql("select * from default.db_test")
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print(spark.sql("SELECT * FROM warehouse1 limit 5").show())
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# connection = engine.connect()
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# 执行Spark SQL查询
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# result = connection.execute("SELECT * FROM warehouse")
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@@ -1,10 +1,11 @@
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from typing import List
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from fastapi import APIRouter
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from pilot.component import ComponentType
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from pilot.configs.config import Config
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from pilot.model.base import ModelInstance, WorkerApplyType
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from pilot.model.cluster import WorkerStartupRequest, WorkerManager
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from pilot.model.cluster import WorkerStartupRequest
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from pilot.openapi.api_view_model import Result
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from pilot.server.llm_manage.request.request import ModelResponse
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@@ -21,15 +22,21 @@ async def model_params():
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worker_manager = CFG.SYSTEM_APP.get_component(
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ComponentType.WORKER_MANAGER_FACTORY, WorkerManagerFactory
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).create()
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return Result.succ(await worker_manager.supported_models())
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params = []
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workers = await worker_manager.supported_models()
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for worker in workers:
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for model in worker.models:
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model_dict = model.__dict__
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model_dict["host"] = worker.host
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model_dict["port"] = worker.port
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params.append(model_dict)
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return Result.succ(params)
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if not worker_instance:
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return Result.faild(code="E000X", msg=f"can not find worker manager")
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except Exception as e:
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return Result.faild(code="E000X", msg=f"model stop failed {e}")
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@router.get("/v1/worker/model/list")
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async def model_list():
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print(f"/worker/model/list")
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@@ -81,6 +88,7 @@ async def model_start(request: WorkerStartupRequest):
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instances = await controller.get_all_instances(
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model_name="WorkerManager@service", healthy_only=True
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)
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request.params = {}
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worker_instance = None
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for instance in instances:
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if instance.host == request.host and instance.port == request.port:
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