I have an MLLib model saved in a folder on S3, say bucket-name/test-model. Now, I have a spark cluster (let's say on a single machine for now). I am running the following commands to load the model:
pyspark --packages com.amazonaws:aws-java-sdk:1.7.4,org.apache.hadoop:hadoop-aws:2.7.3
Then,
sc.setSystemProperty("com.amazonaws.services.s3.enableV4", "true")
hadoopConf = sc._jsc.hadoopConfiguration()
hadoopConf.set("fs.s3a.awsAccessKeyId", AWS_ACCESS_KEY)
hadoopConf.set("fs.s3a.awsSecretAccessKey", AWS_SECRET_KEY)
hadoopConf.set("fs.s3a.endpoint", "s3.us-east-1.amazonaws.com")
hadoopConf.set("com.amazonaws.services.s3a.enableV4", "true")
hadoopConf.set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
from pyspark.ml.classification import RandomForestClassifier, RandomForestClassificationModel
m1 = RandomForestClassificationModel.load('s3a://test-bucket/test-model')
and I get the following error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/user/.local/lib/python3.6/site-packages/pyspark/ml/util.py", line 362, in load
return cls.read().load(path)
File "/home/user/.local/lib/python3.6/site-packages/pyspark/ml/util.py", line 300, in load
java_obj = self._jread.load(path)
File "/home/user/.local/lib/python3.6/site-packages/pyspark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
File "/home/user/.local/lib/python3.6/site-packages/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/home/user/.local/lib/python3.6/site-packages/pyspark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o35.load.
: com.amazonaws.AmazonClientException: Unable to load AWS credentials from any provider in the chain
at com.amazonaws.auth.AWSCredentialsProviderChain.getCredentials(AWSCredentialsProviderChain.java:117)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3521)
at com.amazonaws.services.s3.AmazonS3Client.headBucket(AmazonS3Client.java:1031)
at com.amazonaws.services.s3.AmazonS3Client.doesBucketExist(AmazonS3Client.java:994)
at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:297)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:258)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1343)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.take(RDD.scala:1337)
at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1378)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.first(RDD.scala:1377)
at org.apache.spark.ml.util.DefaultParamsReader$.loadMetadata(ReadWrite.scala:615)
at org.apache.spark.ml.tree.EnsembleModelReadWrite$.loadImpl(treeModels.scala:427)
at org.apache.spark.ml.classification.RandomForestClassificationModel$RandomForestClassificationModelReader.load(RandomForestClassifier.scala:316)
at org.apache.spark.ml.classification.RandomForestClassificationModel$RandomForestClassificationModelReader.load(RandomForestClassifier.scala:306)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Honestly, these lines of code are taken from the web and I have no idea about storing and loading MLLib models on to S3. Any help here will be appreciated and also the next step for me is to do the same on a cluster of machines. So any heads up will also be appreciated.
You are using the wrong property names for the s3a connector.
see https://hadoop.apache.org/docs/current3/hadoop-aws/tools/hadoop-aws/#Authentication_properties
Specifically:
fs.s3a.access.key your access keyfs.s3a.secret.key your secret keyNote in particular
The mixedCaseOptions are from the s3n connector which is obsolete and has long been deleted from the hadoop codebase. the s3a connector will simply ignore them