from pyspark.sql import types# col 名valuedf = spark.createDataFrame([1, 2, 3, 3, 4], types.IntegerType())# col 为iddf_small = spark.range(3)# 广播df_b = broadcast(df_small)df.join(df_b, df.value == df_small.id).show()+---+---+|value| id|+---+---+| 1| 1||...
介绍pyspark.sql.functions中的常用函数。 官方链接https://spark.apache.org/docs/latest/api/python/reference/index.html SparkSession配置,导入pyspark包 spark.stop()spark=SparkSession\.builder\.appName('pyspark_test')\.config('spark.sql.broadcastTimeout',36000)\.config('spark.executor.memory','2G')...
如果一个表很小,可以使用广播 join 来避免数据倾斜。 代码语言:python 代码运行次数:0 运行 AI代码解释 frompyspark.sql.functionsimportbroadcast small_df=spark.read.csv("small_table.csv")large_df=spark.read.csv("large_table.csv")result=large_df.join(broadcast(small_df),"key_column") 4.使用盐值...
from pyspark.sql.functions import broadcast # 使用广播变量优化连接 joined_df = df1.join(broadcast(df2), on=join_column, how="inner") 参考链接 PySpark Documentation Spark SQL Documentation 通过上述方法,可以在 PySpark 中灵活地动态生成连接条件,并根据需要进行优化。
from pyspark.sql.functions import col, broadcast # 导入 col 和 broadcast @time_decorator 装饰器 def have_broadcast_var(data): small_data = [("CA", "加利福尼亚"), ("TX", "德克萨斯"), ("FL", "佛罗里达")] small_df = spark.createDataFrame(small_data, ["state", "stateFullName"]) ...
12 pyspark.sql.functions.avg(col) 13 pyspark.sql.functions.base64(col) 14 pyspark.sql.functions.bin(col) 15 pyspark.sql.functions.bitwiseNOT(col) 16 pyspark.sql.functions.broadcast(df) 17 pyspark.sql.functions.cbrt(col) 18 pyspark.sql.functions.ceil(col) 19 pyspark.sql.functions.coalesce(*...
1. 使用 Broadcast Join 对于小数据集,可以使用广播连接,将小数据集广播到每个 Executor 节点。以下是使用broadcast()的示例代码: frompyspark.sqlimportSparkSessionfrompyspark.sqlimportfunctionsasFfrompyspark.sql.functionsimportbroadcast spark=SparkSession.builder.appName("Example").getOrCreate()# 创建两个示例 ...
另外在大表join小表时候,可以使用broadcast来进行加速 import org.apache.spark.sql.functions.broadcast val joinExpr = person.col("graduate_program") === graduateProgram.col("id") person.join(broadcast(graduateProgram), joinExpr).explain()发布
from pyspark.sql.functions import broadcast df = large_df.join(broadcast(small_df), "id") ReplacegroupBy().agg()withreduceByKey()ormapPartitions()in RDDs if performance is critical and transformations are simple. Cache Strategically If you’re reusing a DataFrame multiple times in a pipeline,...
pyspark.sql.functions DataFrame可用的内置函数 pyspark.sql.types 可用的数据类型列表 pyspark.sql.Window 用于处理窗口函数 1.class pyspark.sql.types.DataType 数据类型的基类。 1.1 fromInternal(obj) 将内部SQL对象转换为本机Python对象。 1.2 json() ...