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Spark快速大数据分析(第2版)
book

Spark快速大数据分析(第2版)

by Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee
November 2021
Intermediate to advanced
340 pages
10h 46m
Chinese
Posts & Telecom Press
Content preview from Spark快速大数据分析(第2版)
Spark SQL
DataFrame
读写外部数据源
115
我们用一个示例来帮助你理解这些属性的用法。假设使用如下设置。
numPartitions: 10
lowerBound: 1000
upperBound: 10000
分区步长为
1000
,共有
10
个分区。这与分别执行以下
10
条查询等价(每条对应一个分区)。
SELECT * FROM table WHERE partitionColumn BETWEEN 1000 and 2000
SELECT * FROM table WHERE partitionColumn BETWEEN 2000 and 3000
...
SELECT * FROM table WHERE partitionColumn BETWEEN 9000 and 10000
以下是设置这些连接属性时的一些注意点,虽然不是面面俱到,但还是有必要牢记在心。
选择
numPartitions
的取值时,最好先使用
Spark
工作节点数量的整数倍。如果有
4
工作节点,那么可以从
4
8
个分区开始测试
。源系统处理读请求的能力也是关键因素
之一。对于有处理窗口的系统,可以将源系统的请求并发度最大化;对于没有处理窗口
的系统(比如连续处理数据的
OL
TP
系统),应该减少并发请求的数量,以避免耗尽源
系统的资源。
一开始,
lowerBound
upperBound
的取值最好根据
partitionColumn
实际
最大值和最
小值来确定。如果设置了
{numPartitions:10, ...
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Publisher Resources

ISBN: 9787115576019