我是apache spark的新手,显然我在我的macbook中用自制软件安装了apache-spark:
Last login: Fri Jan 8 12:52:04 on console
user@MacBook-Pro-de-User-2:~$ pyspark
Python 2.7.10 (default, Jul 13 2015, 12:05:58)
[GCC 4.2.1 Compatible Apple LLVM 6.1.0 (clang-602.0.53)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
16/01/08 14:46:44 INFO SparkContext: Running Spark version 1.5.1
16/01/08 14:46:46 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/01/08 14:46:47 INFO SecurityManager: Changing view acls to: user
16/01/08 14:46:47 INFO SecurityManager: Changing modify acls to: user
16/01/08 14:46:47 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(user); users with modify permissions: Set(user)
16/01/08 14:46:50 INFO Slf4jLogger: Slf4jLogger started
16/01/08 14:46:50 INFO Remoting: Starting remoting
16/01/08 14:46:51 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://[email protected]:50199]
16/01/08 14:46:51 INFO Utils: Successfully started service 'sparkDriver' on port 50199.
16/01/08 14:46:51 INFO SparkEnv: Registering MapOutputTracker
16/01/08 14:46:51 INFO SparkEnv: Registering BlockManagerMaster
16/01/08 14:46:51 INFO DiskBlockManager: Created local directory at /private/var/folders/5x/k7n54drn1csc7w0j7vchjnmc0000gn/T/blockmgr-769e6f91-f0e7-49f9-b45d-1b6382637c95
16/01/08 14:46:51 INFO MemoryStore: MemoryStore started with capacity 530.0 MB
16/01/08 14:46:52 INFO HttpFileServer: HTTP File server directory is /private/var/folders/5x/k7n54drn1csc7w0j7vchjnmc0000gn/T/spark-8e4749ea-9ae7-4137-a0e1-52e410a8e4c5/httpd-1adcd424-c8e9-4e54-a45a-a735ade00393
16/01/08 14:46:52 INFO HttpServer: Starting HTTP Server
16/01/08 14:46:52 INFO Utils: Successfully started service 'HTTP file server' on port 50200.
16/01/08 14:46:52 INFO SparkEnv: Registering OutputCommitCoordinator
16/01/08 14:46:52 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/01/08 14:46:52 INFO SparkUI: Started SparkUI at http://192.168.1.64:4040
16/01/08 14:46:53 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
16/01/08 14:46:53 INFO Executor: Starting executor ID driver on host localhost
16/01/08 14:46:53 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 50201.
16/01/08 14:46:53 INFO NettyBlockTransferService: Server created on 50201
16/01/08 14:46:53 INFO BlockManagerMaster: Trying to register BlockManager
16/01/08 14:46:53 INFO BlockManagerMasterEndpoint: Registering block manager localhost:50201 with 530.0 MB RAM, BlockManagerId(driver, localhost, 50201)
16/01/08 14:46:53 INFO BlockManagerMaster: Registered BlockManager
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 1.5.1
/_/
Using Python version 2.7.10 (default, Jul 13 2015 12:05:58)
SparkContext available as sc, HiveContext available as sqlContext.
>>>
我想开始玩,以了解有关MLlib的更多信息。但是,我使用Pycharm在python中编写脚本。问题是:当我去Pycharm并尝试调用pyspark时,Pycharm无法找到该模块。我尝试将路径添加到Pycharm,如下所示:
然后从blog我尝试了这个:
import os
import sys
# Path for spark source folder
os.environ['SPARK_HOME']="/Users/user/Apps/spark-1.5.2-bin-hadoop2.4"
# Append pyspark to Python Path
sys.path.append("/Users/user/Apps/spark-1.5.2-bin-hadoop2.4/python/pyspark")
try:
from pyspark import SparkContext
from pyspark import SparkConf
print ("Successfully imported Spark Modules")
except ImportError as e:
print ("Can not import Spark Modules", e)
sys.exit(1)
并且仍然无法开始使用Pychark与Pycharm,任何想法如何“链接”PyCharm与apache-pyspark?
更新:
然后我搜索apache-spark和python路径以设置Pycharm的环境变量:
apache-spark路径:
user@MacBook-Pro-User-2:~$ brew info apache-spark
apache-spark: stable 1.6.0, HEAD
Engine for large-scale data processing
https://spark.apache.org/
/usr/local/Cellar/apache-spark/1.5.1 (649 files, 302.9M) *
Poured from bottle
From: https://github.com/Homebrew/homebrew/blob/master/Library/Formula/apache-spark.rb
python路径:
user@MacBook-Pro-User-2:~$ brew info python
python: stable 2.7.11 (bottled), HEAD
Interpreted, interactive, object-oriented programming language
https://www.python.org
/usr/local/Cellar/python/2.7.10_2 (4,965 files, 66.9M) *
然后用上面的信息我试着设置环境变量如下:
知道如何正确链接Pycharm与pyspark?
然后,当我运行具有上述配置的python脚本时,我有以下异常:
/usr/local/Cellar/python/2.7.10_2/Frameworks/Python.framework/Versions/2.7/bin/python2.7 /Users/user/PycharmProjects/spark_examples/test_1.py
Traceback (most recent call last):
File "/Users/user/PycharmProjects/spark_examples/test_1.py", line 1, in <module>
from pyspark import SparkContext
ImportError: No module named pyspark
更新:然后我尝试了@ zero323提出的配置
配置1:
/usr/local/Cellar/apache-spark/1.5.1/
出:
user@MacBook-Pro-de-User-2:/usr/local/Cellar/apache-spark/1.5.1$ ls
CHANGES.txt NOTICE libexec/
INSTALL_RECEIPT.json README.md
LICENSE bin/
配置2:
/usr/local/Cellar/apache-spark/1.5.1/libexec
出:
user@MacBook-Pro-de-User-2:/usr/local/Cellar/apache-spark/1.5.1/libexec$ ls
R/ bin/ data/ examples/ python/
RELEASE conf/ ec2/ lib/ sbin/
随着SPARK-1267的合并,您应该能够通过pip
在您用于PyCharm开发的环境中安装Spark来简化流程。
创建运行配置:
SPARK_HOME
- 它应该指向Spark安装目录。它应该包含目录,如bin
(与spark-submit
,spark-shell
等)和conf
(与spark-defaults.conf
,spark-env.sh
等)
PYTHONPATH
- 它应该包含$SPARK_HOME/python
和可选的$SPARK_HOME/python/lib/py4j-some-version.src.zip
否则不可用。 some-version
应匹配给定Spark安装使用的Py4J版本(0.8.2.1 - 1.5,0.9 - 1.6,0.10.3 - 2.0,0.10.4 - 2.1,0.10.4 - 2.2,0.10.6 - 2.3)
将PySpark库添加到解释器路径(代码完成所需):
$SPARK_HOME/python
的路径(如果需要,可以使用Py4J)使用新创建的配置来运行脚本。
我在线跟踪教程并将env变量添加到.bashrc:
# add pyspark to python
export SPARK_HOME=/home/lolo/spark-1.6.1
export PYTHONPATH=$SPARK_HOME/python/:$PYTHONPATH
export PYTHONPATH=$SPARK_HOME/python/lib/py4j-0.9-src.zip:$PYTHONPATH
然后我将SPARK_HOME和PYTHONPATH中的值赋予pycharm:
(srz-reco)lolo@K:~$ echo $SPARK_HOME
/home/lolo/spark-1.6.1
(srz-reco)lolo@K:~$ echo $PYTHONPATH
/home/lolo/spark-1.6.1/python/lib/py4j-0.9-src.zip:/home/lolo/spark-1.6.1/python/:/home/lolo/spark-1.6.1/python/lib/py4j-0.9-src.zip:/home/lolo/spark-1.6.1/python/:/python/lib/py4j-0.8.2.1-src.zip:/python/:
然后我将其复制到脚本的运行/调试配置 - >环境变量。
最简单的方法是
转到anaconda / python安装的site-packages文件夹,复制粘贴pyspark和pyspark.egg-info文件夹。
重启pycharm以更新索引。上面提到的两个文件夹存在于spark安装的spark / python文件夹中。这样你也可以从pycharm获得代码完成建议。
可以在python安装中轻松找到站点包。在anaconda下它的anaconda / lib / pythonx.x / site-packages下
这是我在mac osx上解决这个问题的方法。
brew install apache-spark
export SPARK_VERSION=`ls /usr/local/Cellar/apache-spark/ | sort | tail -1`
export SPARK_HOME="/usr/local/Cellar/apache-spark/$SPARK_VERSION/libexec"
export PYTHONPATH=$SPARK_HOME/python/:$PYTHONPATH
export PYTHONPATH=$SPARK_HOME/python/lib/py4j-0.9-src.zip:$PYTHONPATH
/usr/local/Cellar/apache-spark/1.6.1/libexec/python/lib/py4j-0.9-src.zip
/usr/local/Cellar/apache-spark/1.6.1/libexec/python/lib/pyspark.zip
这是适合我的设置(Win7 64bit,PyCharm2017.3CE)
设置智能感知:
- 单击文件 - >设置 - >项目: - >项目解释器
- 单击Project Interpreter下拉列表右侧的齿轮图标
- 从上下文菜单中单击“更多...”
- 选择解释器,然后单击“显示路径”图标(右下角)
- 单击+图标两个添加以下路径: \ python的\ LIB \ py4j-0.9-src.zip \ BIN \ python的\ LIB \ pyspark.zip
- 单击确定,确定,确定
继续测试您的新intellisense功能。
在pycharm(windows)中配置pyspark
File menu - settings - project interpreter - (gearshape) - more - (treebelowfunnel) - (+) - [add python folder form spark installation and then py4j-*.zip] - click ok
确保在windows环境中设置SPARK_HOME,pycharm将从那里开始。确认 :
Run menu - edit configurations - environment variables - [...] - show
(可选)在环境变量中设置SPARK_CONF_DIR。
我使用以下页面作为参考,并能够获得在PyCharm 5中导入的pyspark / Spark 1.6.1(通过自制软件安装)。
http://renien.com/blog/accessing-pyspark-pycharm/
import os
import sys
# Path for spark source folder
os.environ['SPARK_HOME']="/usr/local/Cellar/apache-spark/1.6.1"
# Append pyspark to Python Path
sys.path.append("/usr/local/Cellar/apache-spark/1.6.1/libexec/python")
try:
from pyspark import SparkContext
from pyspark import SparkConf
print ("Successfully imported Spark Modules")
except ImportError as e:
print ("Can not import Spark Modules", e)
sys.exit(1)
使用上面的,pyspark加载,但是当我尝试创建SparkContext时,我收到网关错误。来自自制软件的Spark存在一些问题,所以我只是从Spark网站上获取Spark(下载为Hadoop 2.6及更高版本预构建)并指向其下的spark和py4j目录。这是pycharm中的代码有效!
import os
import sys
# Path for spark source folder
os.environ['SPARK_HOME']="/Users/myUser/Downloads/spark-1.6.1-bin-hadoop2.6"
# Need to Explicitly point to python3 if you are using Python 3.x
os.environ['PYSPARK_PYTHON']="/usr/local/Cellar/python3/3.5.1/bin/python3"
#You might need to enter your local IP
#os.environ['SPARK_LOCAL_IP']="192.168.2.138"
#Path for pyspark and py4j
sys.path.append("/Users/myUser/Downloads/spark-1.6.1-bin-hadoop2.6/python")
sys.path.append("/Users/myUser/Downloads/spark-1.6.1-bin-hadoop2.6/python/lib/py4j-0.9-src.zip")
try:
from pyspark import SparkContext
from pyspark import SparkConf
print ("Successfully imported Spark Modules")
except ImportError as e:
print ("Can not import Spark Modules", e)
sys.exit(1)
sc = SparkContext('local')
words = sc.parallelize(["scala","java","hadoop","spark","akka"])
print(words.count())
我从这些说明中获得了很多帮助,这些帮助我在PyDev中进行了故障排除,然后让它运行PyCharm - https://enahwe.wordpress.com/2015/11/25/how-to-configure-eclipse-for-developing-with-python-and-spark-on-hadoop/
我敢肯定有人花了几个小时抨击他们的显示器试图让这个工作,所以希望这有助于拯救他们的理智!
我使用conda
来管理我的Python包。所以我在PyCharm外面的终端所做的就是:
conda install pyspark
或者,如果你想要一个早期版本,比如2.2.0,那么:
conda install pyspark=2.2.0
这也会自动拉入py4j。 PyCharm然后不再抱怨import pyspark...
并且代码完成也起作用。注意我的PyCharm项目已经配置为使用Anaconda附带的Python解释器。
假设你的spark python目录是:/home/user/spark/python
假设你的Py4j源是:/home/user/spark/python/lib/py4j-0.9-src.zip
基本上你将spark python目录和py4j目录添加到解释器路径中。我没有足够的声誉来发布屏幕截图或我愿意。
在视频中,用户在pycharm本身内创建虚拟环境,但是,您可以在pycharm之外创建虚拟环境或激活预先存在的虚拟环境,然后使用它启动pycharm并将这些路径添加到虚拟环境解释器路径中。在pycharm内。
我使用其他方法通过bash环境变量添加spark,这在pycharm之外工作得很好,但由于某些原因它们在pycharm中无法识别,但这种方法工作得很好。
在启动IDE或Python之前,需要设置PYTHONPATH,SPARK_HOME。
Windows,编辑环境变量,添加spark python和py4j
PYTHONPATH=%PYTHONPATH%;{py4j};{spark python}
Unix的,
export PYTHONPATH=${PYTHONPATH};{py4j};{spark/python}
要在Python中运行Spark应用程序,请使用位于Spark目录中的bin / spark-submit脚本。此脚本将加载Spark的Java / Scala库,并允许您将应用程序提交到群集。您还可以使用bin / pyspark来启动交互式Python shell。
您正在使用CPython解释器直接调用您的脚本,我认为这会导致问题。
尝试运行您的脚本:
"${SPARK_HOME}"/bin/spark-submit test_1.py
如果有效,你应该能够通过将项目的解释器设置为spark-submit来使它在PyCharm中工作。