1966/efficient-way-read-specific-columns-from-parquet-file-spark
As parquet is a column based storage file, so
val df = spark.read.parquet("fs://path/file.parquet"),load(<parquet>).select(...)
is the best option
Hey, You can try this: from pyspark import SparkContext SparkContext.stop(sc) sc ...READ MORE
Refer to the below code: import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.FileSystem import ...READ MORE
Yes, you can go ahead and write ...READ MORE
Hi! I found 2 links on github where ...READ MORE
Parquet is a columnar format file supported ...READ MORE
Parquet is a columnar format supported by ...READ MORE
The official definition of Apache Hadoop given ...READ MORE
For accessing Hadoop commands & HDFS, you ...READ MORE
In your log4j.properties file you need to ...READ MORE
its late but this how you can ...READ MORE
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