Hey Dylan, Great!
Can you revert back to my initial and also the latest mail? Thanks, Aakash. On 15-Mar-2018 12:27 AM, "Dylan Guedes" <djmggue...@gmail.com> wrote: > Hi, > > I've been using the Kafka with pyspark since 2.1. > > On Wed, Mar 14, 2018 at 3:49 PM, Aakash Basu <aakash.spark....@gmail.com> > wrote: > >> Hi, >> >> I'm yet to. >> >> Just want to know, when does Spark 2.3 with 0.10 Kafka Spark Package >> allows Python? I read somewhere, as of now Scala and Java are the languages >> to be used. >> >> Please correct me if am wrong. >> >> Thanks, >> Aakash. >> >> On 14-Mar-2018 8:24 PM, "Georg Heiler" <georg.kf.hei...@gmail.com> wrote: >> >>> Did you try spark 2.3 with structured streaming? There watermarking and >>> plain sql might be really interesting for you. >>> Aakash Basu <aakash.spark....@gmail.com> schrieb am Mi. 14. März 2018 >>> um 14:57: >>> >>>> Hi, >>>> >>>> >>>> >>>> *Info (Using):Spark Streaming Kafka 0.8 package* >>>> >>>> *Spark 2.2.1* >>>> *Kafka 1.0.1* >>>> >>>> As of now, I am feeding paragraphs in Kafka console producer and my >>>> Spark, which is acting as a receiver is printing the flattened words, which >>>> is a complete RDD operation. >>>> >>>> *My motive is to read two tables continuously (being updated) as two >>>> distinct Kafka topics being read as two Spark Dataframes and join them >>>> based on a key and produce the output. *(I am from Spark-SQL >>>> background, pardon my Spark-SQL-ish writing) >>>> >>>> *It may happen, the first topic is receiving new data 15 mins prior to >>>> the second topic, in that scenario, how to proceed? I should not lose any >>>> data.* >>>> >>>> As of now, I want to simply pass paragraphs, read them as RDD, convert >>>> to DF and then join to get the common keys as the output. (Just for R&D). >>>> >>>> Started using Spark Streaming and Kafka today itself. >>>> >>>> Please help! >>>> >>>> Thanks, >>>> Aakash. >>>> >>> >
