from pyspark import SparkContext, SparkConf from pyspark.sql.dataframe import DataFrame from pyspark.sql.session import SparkSession import json from pyspark.sql import HiveContext from pyspark.sql import SQLContext sparkconf = SparkConf().setAppName("Python Spark2").set("spark.ui.showConsoleProgres...
删掉下游表,在 Hive 中直接创建。然后将写入逻辑改为INSERT OVERWRITE TABLE,发现问题解决。修改后类似于: df = spark.sql(...) df = spark.createDataFrame(df.rdd.map(function_name), ...) df.createOrReplaceTempView("<middle_name>") spark.sql("INSERT OVERWRITE TABLE test. SELECT * FROM <middle...
# 写入表,写入上述创建的临时表 insert_sql = ''' insert overwrite table temp.hh_mult_write_{i} select questionid from temp.hh_qids where ceil(rn/10000000)={i} order by questionid limit 100000000 ''' 循环写入 %%time # 通过循环创建多个临时表并写入 for i in range(1,math.ceil(N/...
sql_hive_insert = ''' insert overwrite table temp.hive_mysql select 1 as id, 'A' as dtype, 10 as cnt union all select 2 as id, 'B' as dtype, 23 as cnt ''' spark.sql(sql_hive_insert) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 DataFrame[] 读取hive表 代码语言:javascr...
hive_sql.sql('''insert overwrite table test_youhua.test_spark_create_tbl1 select * from test_youhua.youhua1''') 再提交 [root@hadoop02 spark]# spark-submit input/test_pyspark_hive.py 可以看到操作成功:
sql(sql_hive_create) DataFrame[] 写入hive表 sql_hive_insert = ''' insert overwrite table temp.hive_mysql select 1 as id, 'A' as dtype, 10 as cnt union all select 2 as id, 'B' as dtype, 23 as cnt ''' spark.sql(sql_hive_insert) DataFrame[]...
sqlContext.sql("create table default.write_test select * from test_hive") 或者: #df 转为临时表/临时视图df.createOrReplaceTempView("df_tmp_view")#spark.sql 插入hivespark.sql(""insert overwrite table XXXXX#表名partition(分区名称=分区值)#多个分区按照逗号分开select ...
DataFrame: 要插入数据的DataFrame。 mode(saveMode): 指定写入模式,例如append、overwrite、error或ignore。 tableName: 目标表的名称。3. 使用insertInto的PySpark示例 以下是一个使用insertInto方法的完整PySpark示例: python from pyspark.sql import SparkSession from pyspark.sql import Row # 创建Spark Session spa...
now().strftime("%y/%m/%d %H:%M:%S"), "测试数据写入到表" + save_table) # 方式2.2: 注册为临时表,使用SparkSQL来写入分区表 Spark_df.createOrReplaceTempView("tmp_table") write_sql = """ insert overwrite table {0} partitions (pt_date='{1}') select * from tmp_table """.format(...
insertInto 不会对scheam进行校验,按位置插入 d2.show()+---+---+|name1|age1|+---+---+|ldsx1| 2||ldsx2| 3|+---+---+d2.write.insertInto('ldsx_test')d2.schemaStructType([StructField('name1', StringType(), True), StructField('age1', LongType(), True)]) 本文系转载,版...