Thanks Jerry for the clarification.
Ajay.
On Thu, Jul 11, 2019 at 12:48 PM Jerry Vinokurov
wrote:
> Hi Ajay,
>
> When a Spark SQL statement references a table, that table has to be
> "registered" first. Usually the way this is done is by reading in a
> DataFrame, then calling the createOrRepla
Hi Ajay,
When a Spark SQL statement references a table, that table has to be
"registered" first. Usually the way this is done is by reading in a
DataFrame, then calling the createOrReplaceTempView (or one of a few other
functions) on that data frame, with the argument being the name under which
yo
Sorry, i guess i hit the send button too soon
This question is regarding a spark stand-alone cluster. My understanding is
spark is an execution engine and not a storage layer.
Spark processes data in memory but when someone refers to a spark table
created through sparksql(df/rdd) what exactly
This is stand-alone spark cluster. My understanding is spark is an
execution engine and not a storage layer.
Spark processes data in memory but when someone refers to a spark table
created through sparksql(df/rdd) what exactly are they referring to?
Could it be a Hive table? If yes, is it the same
rning process :-)
Plus IMHO , if u r planning on learning Spark, I would say YES to Scala and NO
to Java. Yes its a diff paradigm but being a Java and Hadoop programmer for
many years, I am excited to learn Scala as the language and use Spark. Its
exciting.
regards
sanjay
From: Aniket Bh
Go through spark API documentation. Basically you have to do group by
(date, message_type) and then do a count.
On Sun, Jan 4, 2015, 9:58 PM Dinesh Vallabhdas
wrote:
> A spark cassandra newbie question. Thanks in advance for the help.
> I have a cassandra table with 2 columns message_timestamp(t
OP 1
2014-06-25 PAUSE 1
2014-06-27 START 2
2014-06-27 STOP 1
2014-06-27 PAUSE 1
2014-06-27 REWIND 2
2014-06-27 RESTART 1
I'm not proficient in scala and would like to use java.
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A spark cassandra newbie question. Thanks in advance for the help.I have a
cassandra table with 2 columns message_timestamp(timestamp) and
message_type(text). The data is of the form2014-06-25 12:01:39 "START"
2014-06-25 12:02:39 "START"
2014-06-25 12:02:39 "PAUSE"
2014-06-25 14:02:39 "STOP"
2014
