TypeError: 'JavaPackage' object is not callable

[pohutukawa]

Whenever I try to use Flint here locally (no Hadoop/EMR involved), it keep barfing at me with the above error message in the subject. It's a setup on top of Python 3.7 with PySpark 2.4.4 and OpenJDK 8; an Ubuntu 19.04 install.

Note: As I'm running locally only, I'm getting this log message from Spark, but everything does run perfectly using vanilla PySpark:

19/10/23 09:59:50 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

It happens when I try to either read a PySpark dataframe into a ts.flint.TimeSeriesDataFrame. This example is adapted from the Flint Example.ipynb:

import pyspark
import ts.flint
from ts.flint import FlintContext

sc = pyspark.SparkContext('local', 'Flint Example')
spark = pyspark.sql.SparkSession(sc)
flint_context = FlintContext(spark)

sp500 = (
    spark.read
    .option('header', True)
    .option('inferSchema', True)
    .csv('sp500.csv')
    .withColumnRenamed('Date', 'time')
)
sp500 = flint_context.read.dataframe(sp500)

The last line causes the "boom", with this (first part of) the stack trace:

TypeError                                 Traceback (most recent call last)
~/.virtualenvs/pyspark-test/lib/python3.7/site-packages/ts/flint/java.py in new_reader(self)
     37         try:
---> 38             return utils.jvm(self.sc).com.twosigma.flint.timeseries.io.read.TSReadBuilder()
     39         except TypeError:

TypeError: 'JavaPackage' object is not callable

Any ideas what may be going wrong and how the problem could be solved?

[pohutukawa]

Digging deeper around here, it seems like there's an issue with PySpark 2.4 (issue #63, addressed in unmerged pull-request #64). Though the README.md clearly states that flint is already compatible with PySpark 2.4 with Python >= 3.5.

Besides that issue, looking also more closely at the README.md, I'm of the opinion that the install instructions are lacking. I only just did the pip install ts-flint thing, and nothing else. The instructions on ts-flint.readthedocs.io do not even mention anything at all, leading me to the assumption that a pip install is sufficient. The only thing in the README mentioned is that some Scala artifact available from Maven Central is required, though I'm not interested in building ts-flint, but just using it.

Anyway, just following the Maven Central link takes me somewhere, but I've got no idea on how/what to download and where to place it. I presume some JAR file(s) will be required. But how???

Any help would be appreciated for someone quite well informed on Python, OK on Java, but not well at all in the Scala eco-system. Stuff like that would be also awesome to find (both) in the README and the ReadTheDocs piece.

[pohutukawa]

Update: I got part way further.

I have tracked down the flint-0.6.0.jar file to download off of Maven Central. I have placed it in my virtual environment's lib/python3.7/site-packages/pyspark/jars/ directory, and the TypeError mentioned in this issue's title disappears, and the code sample given above works.

But moving on forward still gave problems. Now I was getting a

py4j.protocol.Py4JJavaError: An error occurred while calling o97.showString.

Solution to this problem was to grab the correct version (fitting the Scala version Spark uses) off of Maven Central (e.g. here https://mvnrepository.com/artifact/org.clapper/grizzled-slf4j_2.11/1.3.4) and place it in the same jars/ directory mentioned above.

Doing so I got (after the adaptation below for getting spark into the notebook) almost all things to work from the Flint Example.ipynb:

import pyspark
sc = pyspark.SparkContext('local', 'Flint Example')
spark = pyspark.sql.SparkSession(sc)

The only thing still coughing up an error is the computation of sp500_decayed_return. I'll see if I can get that to work somehow as well.

It may be useful to mention some of these things in the install instructions. Most Python/data science practitioners are not quite developers who are into building such artifacts from Scala sources, but would happily be able to do a hearty pip install ts-flint and think they're done.

[vkrot]

Actually README mentions:

You can use ts-flint with PySpark by:

pyspark --jars /path/to/flint-assembly-{VERSION}-SNAPSHOT.jar --py-files /path/to/flint-assembly-{VERSION}-SNAPSHOT.jar

For me adding --jars and --py-files fixed the problem

[suhrmann]

I'm using MacOS and I installed Spark 2.4.4 with Homebrew. But I used the aproach to add the Flint JAR to lib folder of Spark

Now I'm stuck at the Py4JJavaError as well:

Py4JJavaError: An error occurred while calling o409.concatArrowAndExplode.
: java.lang.NoSuchMethodError: org.apache.spark.sql.catalyst.expressions.codegen.ExprCode.code()Ljava/lang/String;

vkrot's approach did not work for me either

---

When I switched back to Spark 2.3.4 I get this error:

Py4JJavaError: An error occurred while calling o420.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 1 times, most recent failure: Lost task 0.0 in stage 8.0 (TID 8, localhost, executor driver): org.apache.spark.util.TaskCompletionListenerException: Memory was leaked by query. Memory leaked: (4096)
Allocator(ROOT) 0/4096/4096/9223372036854775807 (res/actual/peak/limit)

---

1. To use Flint first I downloaded flint-0.6.0.jar directly from Maven Repsoitory for Flint into the libexec/jars directory of Spark:

   /usr/local/Cellar/apache-spark/2.4.4/libexec/jars

   Note: I also had to download missing dependency grizzled-slf4j_2.11 - Check Compile Dependencies in Maven Repository of Flint for other missing dependencies

2. Then I installed Python artifact with pip:

   pip install ts-flint

3. Now I can simply invoke pyspark or spark-submit without parameters --jars and --py-files

[eromoe]

@pohutukawa I have same problem, did you find a solution ?

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~/.conda/envs/py3/lib/python3.7/site-packages/ts/flint/java.py in new_reader(self)
     37         try:
---> 38             return utils.jvm(self.sc).com.twosigma.flint.timeseries.io.read.TSReadBuilder()
     39         except TypeError:

TypeError: 'JavaPackage' object is not callable

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-12-87fea234d827> in <module>
----> 1 df = fc.read.options(timeColumn="ds").parquet(TB.SALECOUNT_OUT, is_sorted=False)

~/.conda/envs/py3/lib/python3.7/site-packages/ts/flint/context.py in read(self)
     82         '''
     83 
---> 84         return readwriter.TSDataFrameReader(self)

~/.conda/envs/py3/lib/python3.7/site-packages/ts/flint/readwriter.py in __init__(self, flintContext)
     49         self._sqlContext = self._flintContext._sqlContext
     50         self._jpkg = java.Packages(self._sc)
---> 51         self._reader = self._jpkg.new_reader()
     52         self._parameters = self._reader.parameters()
     53 

~/.conda/envs/py3/lib/python3.7/site-packages/ts/flint/java.py in new_reader(self)
     38             return utils.jvm(self.sc).com.twosigma.flint.timeseries.io.read.TSReadBuilder()
     39         except TypeError:
---> 40             return utils.jvm(self.sc).com.twosigma.flint.timeseries.io.read.ReadBuilder()
     41 
     42     @property

TypeError: 'JavaPackage' object is not callable

[eromoe]

OK, I figure it out . My problem seems mainly caused by jupyter/spark session cache .

Restart jupyter notebook and create a fresh new spark session with {"spark.jars" : "hdfs://maskxdc/test/flint-0.6.0.jar" } solve the problem .

It actually only need config spark.jars .

[Maria-UET]

I was facing the same problem with Pyarrow.

My environment:

• Python 3.6
• Pyspark 2.4.4
• Pyarrow 4.0.1
• Jupyter notebook
• Spark cluster on GCS

When I try to enable Pyarrow optimization like this: spark.conf.set('spark.sql.execution.arrow.enabled', 'true)

I get the following warning: createDataFrame attempted Arrow optimization because 'spark.sql.execution.arrow.enabled' is set to true; however failed by the reason below: TypeError: 'JavaPackage' object is not callable

I solved this problem by:

1. I printed the config of spark session:

   
   import  os
   from pyspark import SparkConf

spark_config = SparkConf().getAll() for conf in spark_config: print(conf)

This will print the key-value pairs of spark configurations. 

2. I found the path to my jar files in this key-value pair:
`('spark.yarn.jars', 'path\to\jar\files')`

3. After I found the path where my jar files are located, I printed the names of jars for Pyarrow, like this:

jar_names = os.listdir('path\to\jar\files') for jar_name in jar_names: if 'arrow' in jar_name: print(jar_name)

I found the following jars:

arrow-format-0.10.0.jar arrow-memory-0.10.0.jar arrow-vector-0.10.0.jar

4. Then I added the path of arrow jars in the spark session config:
For adding multiple jar file paths, I used : as delimiter.
`spark.conf.set('spark.driver.extraClassPath', 'path\to\jar\files\arrow-format-0.10.0.jar:path\to\jar\files\arrow-memory-0.10.0.jar:path\to\jar\files\arrow-vector-0.10.0.jar')`

5. Then I restarted the kernel and Pyarrow optimization worked