Apache Spark SQL 需要永远计算来自 Cassandra 的十亿行? [英] Apache Spark SQL is taking forever to count billion rows from Cassandra?
问题描述
我有以下代码
我调用 spark-shell 如下
I invoke spark-shell as follows
./spark-shell --conf spark.cassandra.connection.host=170.99.99.134 --executor-memory 15G --executor-cores 12 --conf spark.cassandra.input.split.size_in_mb=67108864
代码
scala> val df = spark.sql("SELECT test from hello") // Billion rows in hello and test column is 1KB
df: org.apache.spark.sql.DataFrame = [test: binary]
scala> df.count
[Stage 0:> (0 + 2) / 13] // I dont know what these numbers mean precisely.
如果我调用 spark-shell 如下
If I invoke spark-shell as follows
./spark-shell --conf spark.cassandra.connection.host=170.99.99.134
代码
val df = spark.sql("SELECT test from hello") // This has about billion rows
scala> df.count
[Stage 0:=> (686 + 2) / 24686] // What are these numbers precisely?
这两个版本都不起作用 Spark 一直在运行,我已经等了 15 多分钟没有响应.关于可能出什么问题以及如何解决此问题的任何想法?
Both of these versions didn't work Spark keeps running forever and I have been waiting for more than 15 mins and no response. Any ideas on what could be wrong and how to fix this?
我使用的是 Spark 2.0.2和 spark-cassandra-connector_2.11-2.0.0-M3.jar
I am using Spark 2.0.2 and spark-cassandra-connector_2.11-2.0.0-M3.jar
推荐答案
Dataset.count
很慢,因为它在涉及外部数据源时不是很聪明.它将查询重写为(很好):
Dataset.count
is slow because it is not very smart when it comes to external data sources. It rewrites query as (it is good):
SELECT COUNT(1) FROM table
但是它没有按下 COUNT
而是直接执行:
but instead of pushing COUNT
down it just executes :
SELECT 1 FROM table
针对源(在您的情况下它将获取十亿个),然后在本地聚合以获得最终结果.您看到的数字是任务计数器.
against the source (it'll fetch a billion ones in your case) and then aggregates locally to get the final result. Numbers you see are tasks counters.
在CassandraRDD
上有一个优化的cassandraCount
操作:
There is an optimized cassandraCount
operation on CassandraRDD
:
sc.cassandraTable(keyspace, table).cassandraCount
关于服务器端操作的更多信息可以在 文档.
More about server side operations can be found in the documentation.
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