Difference between orc and parquet format 参考: https://www.cnblogs.com/ITtangtang/p/7677912.html https://blog.csdn.net/yu616568/article/details/51868447 https://hortonworks.com/blog/orcfile-in-hdp-2-better-compression-better-performance/ 总结 两者都是参考了Google 的Dremel的数据格式, 列存储, ...
Parquet 对 Hadoop 生态系统中的大多数项目拥有更广泛的支持,但ORC仅支持Hive和Pig。两者之间的一个关键区别是,ORC更好地优化了Hive,而Parquet与Spark配合的更好。事实上,Parquet 是用于在 Apache Spark 中写入和读取数据的默认文件格式。 索引 • 使用 ORC 文件就像处理 Parquet 文件一样简单。两者都非常适合读取...
This means that in a Parquet file format, even the nested fields can be read individually without the need to read all the fields in the nested structure. Parquet format uses the record shredding and assembly algorithm for storing nested structures in columnar fashion....
We initially thought there is a problem with csv library that we are using(spark.csv datasource by databricks) to validate this we just changed the output format to parquet, and we got nearly 10 times performance difference , below is the action where we are inserting into ...
( Also in new hive versions snappy compression is slower or equivalent and much more space hungry than the default zip ) Reply 4,427 Views 2 Kudos 0 joncodin Rising Star Created 05-08-2016 03:32 PM Thanks for your answer, Im using hive 1.2.1. And I read that parquet and ...