Pre-register your classes:
```
import com.esotericsoftware.kryo.Kryo
import org.apache.spark.serializer.KryoRegistrator
class MyKryoRegistrator extends KryoRegistrator {
override def registerClasses(kryo: Kryo): Unit = {
kryo.register(Class.forName("[[B")) // byte[][]
You can do it with custom RDD implementation.
You will mainly implement "getPartitions" - the logic to split your input
into partitions and "compute" to compute and return the values from the
executors.
On Tue, 17 Sep 2019 at 08:47, Marcelo Valle wrote:
> Just to be more clear about my
Just to be more clear about my requirements, what I have is actually a
custom format, with header, summary and multi line blocks. I want to create
tasks per block and no per line.I already have a library that reads an
InputStream and outputs an Iterator of Block, but now I need to integrate
this
Hi,
I want to create a custom RDD which will read n lines in sequence from a
file, which I call a block, and each block should be converted to a spark
dataframe to be processed in parallel.
Question - do I have to implement a custom hadoop input format to achieve
this? Or is it possible to do it
Hi,
If Spark applications write data into alluxio, can WriteType be configured?
Thanks,
Mark
Hi folks,
Posted this some time ago but the problem continues to bedevil us. I'm
including a (slightly edited) stack trace that results from this error. If
anyone can shed any light on what exactly is happening here and what we can
do to avoid it, that would be much appreciated.
Spark mllib library Streaming Training models work with DStream. So is
there any way to use them with spark structured streaming.
So I am trying to integrate MLeap to spark structured streaming, But facing
a problem. As the Spark structured Streaming with Kafka works with data
frames and for MLeap LeapFrame is required. So I tried to convert data
frame to leapframe using mleap spark support library function
I want to parse the Struct of data dynamically , then write data to delta lake
, I think it can automatically merge scheme.
2019-09-17
lk_spark
发件人：Tathagata Das
发送时间：2019-09-17 16:13
主题：Re: how can I dynamic parse json in kafka when using Structured Streaming
收件人："lk_spark"
You can use *from_json* built-in SQL function to parse json.
https://spark.apache.org/docs/latest/api/java/org/apache/spark/sql/functions.html#from_json-org.apache.spark.sql.Column-org.apache.spark.sql.Column-
On Mon, Sep 16, 2019 at 7:39 PM lk_spark wrote:
> hi,all :
> I'm using Structured
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