接下来,我们可以执行多条 SQL 查询,通常是通过循环或存储在列表中的方式一次性执行。 # 定义 SQL 查询列表sql_queries=["SELECT * FROM my_table WHERE age > 30","SELECT COUNT(*) FROM my_table","SELECT name, COUNT(*) FROM my_table GROUP BY name"]# 执行 SQL 查询results=[]forqueryinsql_que...
from pyspark.sql import SparkSession # 创建SparkSession spark = SparkSession.builder \ .appName("Spark SQL Example") \ .getOrCreate() # 读取SQL文件内容 with open('queries.sql', 'r') as file: sql_queries = file.read() # 分割SQL语句并执行 for query in sql_queries.split(';'): query...
# 要执行的SQL语句列表 sql_queries = [ "SELECT * FROM people WHERE Age > 25", "SELECT Name, COUNT(*) as Count FROM people GROUP BY Name", "SELECT AVG(Age) as AverageAge FROM people" ] # 循环执行每个SQL语句并显示结果 for query in sql_queries: result = spark.sql(query) result.sho...
# The results of SQL queries are Dataframe objects. # rdd returns the content as an :class:`pyspark.RDD` of :class:`Row`. teenNames = teenagers.rdd.map( lambda p: "Name: " + ).collect() for name in teenNames: print(name) # Name: Justin 1. 2. 3. 4. 5. 6. 7. 8. 9. ...
处理数据的输入输出,从不同数据源(结构化数据 Parquet 文件 JSON 文件、Hive 表、外部数据库、已有 RDD)获取数据,执行查询(expression of queries),并将查询结果输出成 DataFrame。 Hive 支持: 对Hive 数据的处理,主要包括 HiveQL、MetaStore、SerDes、UDFs 等。
# The results of SQL queries are Dataframe objects. # rdd returns the content as an :class:`pyspark.RDD` of :class:`Row`. teenNames = teenagers.rdd.map(lambda p: "Name: " + p.name).collect() for name in teenNames: print(name) ...
Do you want to convert SQL into PySpark Dataframe code ? I created this utility as my weekend project. I was able to convert basic sql queries into pyspark code. I have shared the code used for the project and you are free to use it , customise it as per your requirement. ...
When set to true, Hive Thrift server executes SQL queries in an asynchronous way. spark.sql.hive.thriftServer.singleSession FALSE When set to true, Hive Thrift server is running in a single session mode. All the JDBC/ODBC connections share the temporary views, function registries, SQL configura...
该页上所有的例子使用Spark分布式中的样本数据,可以运行在spark-shell或者pyspark shell中。 创建DataFrames(Creating DataFrames) 使用SQLContext,应用可以从一个已经存在的RDD、Hive表或者数据源中创建DataFrames。 例如,以下根据一个JSON文件创建出一个DataFrame: ...
Users can use these references to enhance their understanding of SQL within the Databricks environment and apply best practices to optimize their queries. Share this: Tweet Share Share on Tumblr WhatsApp More Loading… ←Previous Srini Experienced Data Engineer with expertise in AI, GenAI, PySpark...