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From Ryan Murray <rym...@dremio.com>
Subject Re: Python and Java interoperability
Date Wed, 22 Jul 2020 09:35:10 GMT
Hey Jesse,

This looks like the buffer was not put correctly onto Redis. Java is not
able to deserialize the message. I recommend putting the hex string from
python into redis. You have to be careful about feeding the correct bytes
to arrow from redis so double check the hex str -> bytes deserialization is
ok too.

Best,
Ryan


On Wed, Jul 22, 2020 at 6:49 AM Jesse Wang <hello.wjx@gmail.com> wrote:

>  Hi Ryan,
> Thanks for your reply.
>
> On Tue, Jul 21, 2020 at 8:54 PM Ryan Murray <rymurr@dremio.com> wrote:
>
>> Hey Jiaxing,
>>
>> You want to use the IPC mechanism to pass arrow buffers between
>> languages[1]
>>
>> First get a buffer:
>> ```
>> import pyarrow as pa
>>
>> data = [
>>     pa.array([1, 2, 3, 4]),
>>     pa.array(['foo', 'bar', 'baz', None]),
>>     pa.array([True, None, False, True])
>> ]
>> batch = pa.record_batch(data, names=['f0', 'f1', 'f2'])
>> sink = pa.BufferOutputStream()
>> writer = pa.ipc.new_stream(sink, batch.schema)
>> writer.write_batch(batch)
>> writer.close()
>> buf = sink.getvalue()
>> ```
>>
>> The buffer could be written to Redis, to a file etc. For redis I think
>> `r.set("key", buf.hex())` is easiest, you don't have to worry about
>> encoding.
>>
>> On the java side something like:
>> ```
>>     Jedis jedis = new Jedis();
>>     String buf = jedis.get("key");
>>     RootAllocator rootAllocator = new RootAllocator(Long.MAX_VALUE);
>>     ByteArrayInputStream in = new
>> ByteArrayInputStream(hexStringToByteArray(buf));
>>     ArrowStreamReader stream = new ArrowStreamReader(in, rootAllocator);
>>     VectorSchemaRoot vsr = stream.getVectorSchemaRoot();
>>     stream.loadNextBatch()
>> ```
>> And the VectorSchemaRoot holds the correct Arrow Buffer.
>>
>
> I tested this and get the following exception thrown:
> ```
> Exception in thread “main” java.lang.IllegalArgumentException
>   at java.nio.ByteBuffer.allocate(ByteBuffer.java:334)
>   at
> org.apache.arrow.vector.ipc.message.MessageSerializer.readMessage(MessageSerializer.java:547)
>   at
> org.apache.arrow.vector.ipc.message.MessageChannelReader.readNext(MessageChannelReader.java:58)
>   at
> org.apache.arrow.vector.ipc.ArrowStreamReader.readSchema(ArrowStreamReader.java:132)
>   at
> org.apache.arrow.vector.ipc.ArrowReader.initialize(ArrowReader.java:178)
>   at
> org.apache.arrow.vector.ipc.ArrowReader.ensureInitialized(ArrowReader.java:169)
>   at
> org.apache.arrow.vector.ipc.ArrowReader.getVectorSchemaRoot(ArrowReader.java:62)
>   at Main.main(Main.java:38)
> ```
>
>
>> While Redis will work for this you might find a file or socket a bit more
>> ergonomic in Arrow. The Plasma object store is also an option[2] which you
>> can think of as a primitive Redis specifically for Arrow Buffers. Finally,
>> if you are using Redis as a message bus you might find the Arrow RPC
>> mechanism Arrow Flight is a good choice[3].
>>
> As for the Plasma, It seems it currently limited to a single host... (From
> its source code arrow/cpp/src/plasma/io.cc, it used AF_UNIX socket only)
>
>
>>
>> [1]
>> https://arrow.apache.org/docs/python/ipc.html#writing-and-reading-streams
>> [2] https://arrow.apache.org/docs/python/plasma.html
>> [3] https://arrow.apache.org/blog/2019/10/13/introducing-arrow-flight/
>>
>> On Tue, Jul 21, 2020 at 10:57 AM Jesse Wang <hello.wjx@gmail.com> wrote:
>>
>>> Hi,
>>> I want to have a Java process read the content of DataFrames produced by
>>> a Python process. The Java and Python processes run on different hosts.
>>>
>>> The solution I can think of is to have the Python process serialize the
>>> DataFrame and save it to redis, and have the Java process parse the data.
>>>
>>> The solution I find serializes the DataFrame to 'pybytes':
>>> (from
>>> https://stackoverflow.com/questions/57949871/how-to-set-get-pandas-dataframes-into-redis-using-pyarrow
>>> )
>>> ```
>>>    import pandas as pd
>>>
>>> import pyarrow as paimport redis
>>>
>>> df=pd.DataFrame({'A':[1,2,3]})
>>> r = redis.Redis(host='localhost', port=6379, db=0)
>>>
>>> context = pa.default_serialization_context()
>>> r.set("key", context.serialize(df).to_buffer().to_pybytes())
>>> context.deserialize(r.get("key"))
>>>    A0  11  22  3
>>>
>>> ```
>>>
>>> I wonder if this serialized 'pybytes' can be parsed at the Java end? If
>>> not, how can I achieve this properly?
>>>
>>> Thanks!
>>>
>>> --
>>>
>>> Best Regards,
>>> Jiaxing Wang
>>>
>>>
>>
>
> --
>
> Best Regards,
> Jiaxing Wang
>
>

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