Anyon知道我为什么会在Jupyter Notebooks中收到此错误？？？？我一直在尝试将Tensorflow模型加载到Apache Spark vis SparlFlow中，但似乎无法弄清楚该错误。任何帮助将不胜感激。
第一个Jupyter单元格：
from sparkflow.graph_utils import build_graph
from sparkflow.tensorflow_async import SparkAsyncDL
import tensorflow as tf
from pyspark.ml.feature import VectorAssembler, OneHotEncoder
from pyspark.ml.pipeline import Pipeline
from pyspark.sql import SparkSession
from tensorflow.keras import layers
from tensorflow.keras import losses
第二个Jupyter单元格：
def lstm_model(X_train, y_train):
# Reshapes to input neuron
inputs= keras.Input(shape = (X_train.shape[1], 1))\
#Training Layers
x_1 = layers.LSTM(units=50, return_sequences=True, input_shape=(X_train.shape[1], 1))(inputs)
x_1 = layers.Dropout(0.2)(x_1)
x_1 = layers.LSTM(units = 50, return_sequences = True)(x_1)
x_1 = layers.Dropout(0.2)(x_1)
x_1 = layers.LSTM(units = 50, return_sequences = True)(x_1)
x_1 = layers.Dropout(0.2)(x_1)
x_1 = layers.LSTM(units = 50, return_sequences = True)(x_1)
x_1 = layers.Dropout(0.2)(x_1)
x_1 = layers.Flatten()(x_1)
# 1 output neuron for each column prediction
output = Dense(units=1)(x_1)
return losses.MeanSquaredError(y_train,output)
第三个Jupyter细胞：
def dataframe_input(pandas_dataframe):
train_data = pandas_dataframe[self.column_name].values
# Reshaping to a 2D array
train_data = train_data.reshape(-1,1)
print(train_data.dtype)
print(type(train_data))
print(train_data.shape)
# Feature Scaling
scaler = MinMaxScaler(feature_range=(0, 1))
scaled_train_data =scaler.fit_transform(train_data)
# Initialzing each x_train and y_train datasets for each column
X_train = []
y_train = []
# Appending scaled training data to each dataset
for i in range(self.timesteps, len(train_data)):
X_train.append(scaled_train_data[i - self.timesteps:i, 0])
y_train.append(scaled_train_data[i, 0])
# Numpy array creation, Keras requires numpy arrays for Inputs
X_train, y_train = np.array(X_train, dtype=int), np.array(y_train)
print(X_train.shape)
print(X_train.dtype)
# Reshaping to a 3D matrix (970, 30, 1)
#X_train = np.reshape(X_train, (X_train[0], X_train[1], 1))
print(X_train.shape)
return X_train, y_train
第四个Jupyter单元格（我收到错误消息的地方）：
# Spark Session
# In order to use APIs of SQL, HIVE, and Streaming, no need to create separate contexts as sparkSession includes all the APIs.
spark = SparkSession \
.builder \
.appName("Python Spark SQL basic example") \
.getOrCreate()
# Reading CSVto a Spark DataFrame
df = spark.read.option("inferSchema", "true").csv('"../csv_test_files/stats.csv"')
# Convert the Spark dataframe into a Pandas Dataframe
pandas_dataframe = df.select("*").toPandas()
# Get the input and ouput data for passing to the model
X_train, y_train = dataframe_input(pandas_dataframe)
错误输出：
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-25-5143cc437b69> in <module>
3 spark = SparkSession \
4 .builder \
----> 5 .appName("Python Spark SQL basic example") \
6 .getOrCreate()
7
~/anaconda3/lib/python3.7/site-packages/pyspark/sql/session.py in getOrCreate(self)
171 for key, value in self._options.items():
172 sparkConf.set(key, value)
--> 173 sc = SparkContext.getOrCreate(sparkConf)
174 # This SparkContext may be an existing one.
175 for key, value in self._options.items():
~/anaconda3/lib/python3.7/site-packages/pyspark/context.py in getOrCreate(cls, conf)
365 with SparkContext._lock:
366 if SparkContext._active_spark_context is None:
--> 367 SparkContext(conf=conf or SparkConf())
368 return SparkContext._active_spark_context
369
~/anaconda3/lib/python3.7/site-packages/pyspark/context.py in __init__(self, master, appName, sparkHome, pyFiles, environment, batchSize, serializer, conf, gateway, jsc, profiler_cls)
134 try:
135 self._do_init(master, appName, sparkHome, pyFiles, environment, batchSize, serializer,
--> 136 conf, jsc, profiler_cls)
137 except:
138 # If an error occurs, clean up in order to allow future SparkContext creation:
~/anaconda3/lib/python3.7/site-packages/pyspark/context.py in _do_init(self, master, appName, sparkHome, pyFiles, environment, batchSize, serializer, conf, jsc, profiler_cls)
196
197 # Create the Java SparkContext through Py4J
--> 198 self._jsc = jsc or self._initialize_context(self._conf._jconf)
199 # Reset the SparkConf to the one actually used by the SparkContext in JVM.
200 self._conf = SparkConf(_jconf=self._jsc.sc().conf())
~/anaconda3/lib/python3.7/site-packages/pyspark/context.py in _initialize_context(self, jconf)
304 Initialize SparkContext in function to allow subclass specific initialization
305 """
--> 306 return self._jvm.JavaSparkContext(jconf)
307
308 @classmethod
~/anaconda3/lib/python3.7/site-packages/py4j/java_gateway.py in __call__(self, *args)
1523 answer = self._gateway_client.send_command(command)
1524 return_value = get_return_value(
-> 1525 answer, self._gateway_client, None, self._fqn)
1526
1527 for temp_arg in temp_args:
~/anaconda3/lib/python3.7/site-packages/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.
: java.net.BindException: Can't assign requested address: Service 'sparkDriver' failed after 16 retries (on a random free port)! Consider explicitly setting the appropriate binding address for the service 'sparkDriver' (for example spark.driver.bindAddress for SparkDriver) to the correct binding address.
at java.base/sun.nio.ch.Net.bind0(Native Method)
at java.base/sun.nio.ch.Net.bind(Net.java:461)
at java.base/sun.nio.ch.Net.bind(Net.java:453)
at java.base/sun.nio.ch.ServerSocketChannelImpl.bind(ServerSocketChannelImpl.java:227)
at io.netty.channel.socket.nio.NioServerSocketChannel.doBind(NioServerSocketChannel.java:128)
at io.netty.channel.AbstractChannel$AbstractUnsafe.bind(AbstractChannel.java:558)
at io.netty.channel.DefaultChannelPipeline$HeadContext.bind(DefaultChannelPipeline.java:1283)
at io.netty.channel.AbstractChannelHandlerContext.invokeBind(AbstractChannelHandlerContext.java:501)
at io.netty.channel.AbstractChannelHandlerContext.bind(AbstractChannelHandlerContext.java:486)
at io.netty.channel.DefaultChannelPipeline.bind(DefaultChannelPipeline.java:989)
at io.netty.channel.AbstractChannel.bind(AbstractChannel.java:254)
at io.netty.bootstrap.AbstractBootstrap$2.run(AbstractBootstrap.java:364)
at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:163)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:403)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:463)
at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:858)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
at java.base/java.lang.Thread.run(Thread.java:834)