I get this error every time... I use sparkling water... My conf-file:
***"spark.driver.memory 65g
spark.python.worker.memory 65g
spark.master local[*]"***
The amount of data is about 5 Gb. There is no another information about this error... Does anybody know why it happens? Thank you!
***"ERROR:py4j.java_gateway:Error while sending or receiving.
Traceback (most recent call last):
File "/data/analytics/Spark1.6.1/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 746, in send_command
raise Py4JError("Answer from Java side is empty")
Py4JError: Answer from Java side is empty
ERROR:py4j.java_gateway:An error occurred while trying to connect to the Java server
Traceback (most recent call last):
File "/data/analytics/Spark1.6.1/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 690, in start
self.socket.connect((self.address, self.port))
File "/usr/local/anaconda/lib/python2.7/socket.py", line 228, in meth
return getattr(self._sock,name)(*args)
error: [Errno 111] Connection refused
ERROR:py4j.java_gateway:An error occurred while trying to connect to the Java server
Traceback (most recent call last):
File "/data/analytics/Spark1.6.1/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 690, in start
self.socket.connect((self.address, self.port))
File "/usr/local/anaconda/lib/python2.7/socket.py", line 228, in meth
return getattr(self._sock,name)(*args)
error: [Errno 111] Connection refused
ERROR:py4j.java_gateway:An error occurred while trying to connect to the Java server
Traceback (most recent call last):
File "/data/analytics/Spark1.6.1/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 690, in start
self.socket.connect((self.address, self.port))
File "/usr/local/anaconda/lib/python2.7/socket.py", line 228, in meth
return getattr(self._sock,name)(*args)
error: [Errno 111] Connection refused"***
Have you tried setting spark.executor.memory
and spark.driver.memory
in your Spark configuration file?
See https://stackoverflow.com/a/22742982/5453184 for more info.
Usually, you'll see this error when the Java process get silently killed by the OOM Killer.
The OOM Killer (Out of Memory Killer) is a Linux process that kicks in when the system becomes critically low on memory. It selects a process based on its "badness" score and kills it to reclaim memory. Read more on OOM Killer here.
Increasing spark.executor.memory
and/or spark.driver.memory
values will only make things worse in this case, i.e. you may want to do the opposite!
Other options would be to:
Or, if you're running your driver/workers using docker:
--oom-kill-disable
on your containers, but make sure you understand possible consequences!Read more on --oom-kill-disable
and other docker memory settings here.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With