7;}
> df = df.withColumnRenamed("id", "itemid").withColumnRenamed("category",
> "cateid") \
> .withColumnRenamed('weight', 'score').withColumnRenamed('tag',
> 'item_tags') \
> .withColumnRenamed(&
Yes, Spark in local mode works :)
One tip
If you just start it, then the default settings is one core and 1 GB.
I'm using this func to start spark in local mode to get all cors and max RAM
import multiprocessing
import os
from pyspark.sql import SparkSession
from pyspark import SparkConf, SparkCo
Sure, as stable and available as your machine is. If you don't need fault
tolerance or scale beyond one machine, sure.
On Mon, Oct 31, 2022 at 8:43 AM 张健BJ wrote:
> Dear developers:
> I have a question about the pyspark local
> mode. Can it be used in production and Will it cause unexpected
Dear developers:
I have a question about the pyspark local mode. Can it be used in production
and Will it cause unexpected problems? The scenario is as follows:
Our team wants to develop an etl component based on python language. Data can
be transferred between various data sources.
If there i