01. Day Two Wrap-Up at Spark Summit #theCUBE!. (00:16)
02. Spark's History and Current Place in the Market. (00:49)
03. The Hadoop and Spark Relationship. (02:44)
04. Hadoop, Spark and Noah's Ark. (03:51)
05. Adoption and Maturity of Continuous Application. (05:31)
06. The Flaws of MapReduce Compared to Spark. (08:39)
Track List created with http://www.vinjavideo.com.
--- ---
Will Spark’s continuous app innovation eclipse other data tools? | #SparkSummit
by R. Danes | Jun 8, 2016
Spark 2.0 and continuous application technology are making waves in the industry. It seems to solve so many data problems in one throw that some are questioning how other data players will compete.
John Walls and George Gilbert (@ggilbert41), cohosts of theCUBE, from the SiliconANGLE Media team, spoke about the excitement around the innovation at the Spark Summit at The Hilton San Francisco Union Square. Gilbert said this marks a new point in the journey we’ve traveled from batch to interactive and now to continuous.
“For the first time in 60 years, we’re inventing a new programming model, a new way of interacting with applications where they never stop, they’re always working,” Gilbert said.
Spark pulls ahead of Hadoop
Gilbert said that while Hadoop still has some interesting features to offer, Spark has become the choice for most developers because it is simpler to operate.
“Spark is one singular engine,” he said, explaining that “all those components run the same way; their security works the same way; their high availability works the same way.”
He said that Hadoop is more spread out and complicated to use, and “that worked 10 years ago, but we can do better now.”
A longer runway
Walls broached the dubious fate of MapReduce, saying, “You could see the shelf life. People from a few years back were predicting its end.”
Gilbert agreed, saying that MapReduce was a limited language that “hit the end of its runway,” whereas “Spark is like San Francisco International Airport; the runway is much longer.”
#SparkSummit
#theCUBE
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Day Two Wrap | Spark Summit 2016
01. Day Two Wrap-Up at Spark Summit #theCUBE!. (00:16)
02. Spark's History and Current Place in the Market. (00:49)
03. The Hadoop and Spark Relationship. (02:44)
04. Hadoop, Spark and Noah's Ark. (03:51)
05. Adoption and Maturity of Continuous Application. (05:31)
06. The Flaws of MapReduce Compared to Spark. (08:39)
Track List created with http://www.vinjavideo.com.
--- ---
Will Spark’s continuous app innovation eclipse other data tools? | #SparkSummit
by R. Danes | Jun 8, 2016
Spark 2.0 and continuous application technology are making waves in the industry. It seems to solve so many data problems in one throw that some are questioning how other data players will compete.
John Walls and George Gilbert (@ggilbert41), cohosts of theCUBE, from the SiliconANGLE Media team, spoke about the excitement around the innovation at the Spark Summit at The Hilton San Francisco Union Square. Gilbert said this marks a new point in the journey we’ve traveled from batch to interactive and now to continuous.
“For the first time in 60 years, we’re inventing a new programming model, a new way of interacting with applications where they never stop, they’re always working,” Gilbert said.
Spark pulls ahead of Hadoop
Gilbert said that while Hadoop still has some interesting features to offer, Spark has become the choice for most developers because it is simpler to operate.
“Spark is one singular engine,” he said, explaining that “all those components run the same way; their security works the same way; their high availability works the same way.”
He said that Hadoop is more spread out and complicated to use, and “that worked 10 years ago, but we can do better now.”
A longer runway
Walls broached the dubious fate of MapReduce, saying, “You could see the shelf life. People from a few years back were predicting its end.”
Gilbert agreed, saying that MapReduce was a limited language that “hit the end of its runway,” whereas “Spark is like San Francisco International Airport; the runway is much longer.”
#SparkSummit
#theCUBE
