My DataFrame has the following schema
root
|-- data: struct (nullable = true)
||-- zoneId: string (nullable = true)
||-- deviceId: string (nullable = true)
||-- timeSinceLast: long (nullable = true)
|-- date: date (nullable = true)
How can I do a writeStream with Parquet format
For pyspark specifically IMO should be very high on the list to port back...
As for roadmap - should be sharing more soon.
From: lucas.g...@gmail.com
Sent: Friday, March 2, 2018 9:41:46 PM
To: user@spark.apache.org
Cc: Felix Cheung
Subject: Re: Question on Spark-
Oh interesting, given that pyspark was working in spark on kub 2.2 I
assumed it would be part of what got merged.
Is there a roadmap in terms of when that may get merged up?
Thanks!
On 2 March 2018 at 21:32, Felix Cheung wrote:
> That’s in the plan. We should be sharing a bit more about the
That's in the plan. We should be sharing a bit more about the roadmap in future
releases shortly.
In the mean time this is in the official documentation on what is coming:
https://spark.apache.org/docs/latest/running-on-kubernetes.html#future-work
This supports started as a fork of the Apache Sp
Structured Streaming's file sink solves these problems by writing a
log/manifest of all the authoritative files written out (for any format).
So if you run batch or interactive queries on the output directory with
Spark, it will automatically read the manifest and only process files are
that are in
Hi
Couple of questions:
1. It seems the error is due to number format:
Caused by: java.util.concurrent.ExecutionException:
java.lang.NumberFormatException:
For input string: "0003024_"
at java.util.concurrent.FutureTask.report(FutureTask.java:122)
at java.util.concurrent.Futur
Is there a way to get finer control over file writing in parquet file
writer ?
We've an streaming application using Apache Apex ( on path of migration to
Spark ...story for a different thread). The existing streaming application
read JSON from Kafka and writes Parquet to HDFS. We're trying to deal
Something like this?
sparkSession.experimental.extraStrategies = Seq(Strategy)
val logicalPlan = df.logicalPlan
val newPlan: LogicalPlan = Strategy(logicalPlan)
Dataset.ofRows(sparkSession, newPlan)
On Thu, Mar 1, 2018 at 8:20 PM, Keith Chapman
wrote:
> Hi,
>
> I'd like to write a custom Spa
Hi All,
Greetings ! I needed some help to read a Hive table
via Pyspark for which the transactional property is set to 'True' (In other
words ACID property is enabled). Following is the entire stacktrace and the
description of the hive table. Would you please be able to help
Hello,
I want to read with a single Spark Streaming process several topics. I'm
using avro and the data to the different topics have a different
schema.Ideally, If I would only have one topic I could implement a
deserializer but, I don't know if it's possible with many different schemas.
val kafk
Does the Resource scheduler support dynamic resource allocation? Are there any
plans to add in the future?
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Thanks Alessandro and Christoph. I appreciate the feedback, but I'm still
having issues determining how to actually accomplish this with the API.
Can anyone point me to an example in code showing how to accomplish this?
On Fri, Mar 2, 2018 2:37 AM, Alessandro Solimando
alessandro.solima...
Hi Matt,
similarly to what Christoph does, I first derive the cluster id for the
elements of my original dataset, and then I use a classification algorithm
(cluster ids being the classes here).
For this method to be useful you need a "human-readable" model, tree-based
models are generally a good c
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