from pyspark.sql import SparkSession from pyspark.sql.types import * import pandas as pd from pyspark.sql import Row from datetime import datetime, date #RDD转化为DataFrame spark=SparkSession.builder.appName("jsonRDD").getOrCreate() sc=spark.sparkContext stringJSONRDD=sc.parallelize([ ["123",...
import pandas as pd from pyspark.sql import SparkSession from pyspark.context import SparkContext from pyspark.sql.functions import *from pyspark.sql.types import *from datetime import date, timedelta, datetime import time 2、初始化SparkSession 首先需要初始化一个Spark会话(SparkSession)。通过SparkSessio...
substring(str, pos, len): Substring starts at pos and is of length len when str is String type or returns the slice of byte array that starts at pos in byte and is of length len when str is Binary type. substring_index(str, delim, count): Returns the substring from string str befor...
对5行数据进行startsWith操作和endsWith操作的结果。 5.5、“substring”操作 Substring的功能是将具体索引中间的文本提取出来。在接下来的例子中,文本从索引号(1,3),(3,6)和(1,6)间被提取出来。 dataframe.select(dataframe.author.substr(1 ,3).alias("title")).show(5) dataframe.select(dataframe.author.s...
data3.withColumn("nik_shi", substring(col("nik").cast("string"), 3, 2)).show() # 1. 连接数据 pandas里面主要是merge函数 polars更像sql里面用join #data1.merge(data11, on='key') #data2.join(data22, on='key') #data3.join(data3_with_new, data3["kk"] == data3_with_new["kk...
df: org.apache.spark.sql.DataFrame = [nameid: string] try something like this: df.withColumn("name",substring_index(col("nameid"), "$", 1)).withColumn("id", substring_index(col("nameid"), "$", -1)).show and the output
.remove_attachment_point_numbers, pst.StringType()) results_df =self._initialize_results(initial_scaffolds) scaffolds_df = results_df.select("smiles","scaffold","decorations") i =0while scaffolds_df.count()>0:# generate randomized SMILESself...
import sqlglot -from sqlglot.dataframe.sql.session import SparkSession -from sqlglot.dataframe.sql import functions as F - -dialect = "spark" - -sqlglot.schema.add_table( - 'employee', - { - 'employee_id': 'INT', - 'fname': 'STRING', - 'lname': 'STRING', - 'age': 'INT'...
String Functions # Substring - col.substr(startPos, length)df=df.withColumn('short_id',df.id.substr(0,10))# Trim - F.trim(col)df=df.withColumn('name',F.trim(df.name))# Left Pad - F.lpad(col, len, pad)# Right Pad - F.rpad(col, len, pad)df=df.withColumn('id',F.lpad('id...
Substring >>> df.select(df.firstName.substr(1, 3) \ #Return substrings of firstName .alias("name")) \ .collect() Powered By Between >>> df.select(df.age.between(22, 24)) \ #Show age: values are TRUE if between 22 and 24 .show() Powered By Add, Update & Remove Column...