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Which one of the following statements is FALSE regarding the communication between DataNodes and a federation of NameNodes in Hadoop 2.0?
Each DataNode receives commands from one designated master NameNode.
DataNodes send periodic heartbeats to all the NameNodes.
Each DataNode registers with all the NameNodes.
DataNodes send periodic block reports to all the NameNodes.
A client application creates an HDFS file named foo.txt with a replication factor of 3. Identify which best describes the file access rules in HDFS if the file has a single block that is stored on data nodes A, B and C?
The file will be marked as corrupted if data node B fails during the creation of the file.
Each data node locks the local file to prohibit concurrent readers and writers of the file.
Each data node stores a copy of the file in the local file system with the same name as the HDFS file.
The file can be accessed if at least one of the data nodes storing the file is available.
Examine the following Hive statements:
Assuming the statements above execute successfully, which one of the following statements is true?
Each reducer generates a file sorted by age
The SORT BY command causes only one reducer to be used
The output of each reducer is only the age column
The output is guaranteed to be a single file with all the data sorted by age
When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?
When the types of the reduce operation’s input key and input value match the types of the reducer’s output key and output value and when the reduce operation is both communicative and associative.
When the signature of the reduce method matches the signature of the combine method.
Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.
Never. Combiners and reducers must be implemented separately because they serve different purposes.
You want to run Hadoop jobs on your development workstation for testing before you submit them to your production cluster. Which mode of operation in Hadoop allows you to most closely simulate a production cluster while using a single machine?
Run all the nodes in your production cluster as virtual machines on your development workstation.
Run the hadoop command with the –jt local and the –fs file:///options.
Run the DataNode, TaskTracker, NameNode and JobTracker daemons on a single machine.
Run simldooop, the Apache open-source software for simulating Hadoop clusters.
Which one of the following files is required in every Oozie Workflow application?
Workflows expressed in Oozie can contain:
Sequences of MapReduce and Pig. These sequences can be combined with other actions including forks, decision points, and path joins.
Sequences of MapReduce job only; on Pig on Hive tasks or jobs. These MapReduce sequences can be combined with forks and path joins.
Sequences of MapReduce and Pig jobs. These are limited to linear sequences of actions with exception handlers but no forks.
Iterntive repetition of MapReduce jobs until a desired answer or state is reached.
Which best describes what the map method accepts and emits?
It accepts a single key-value pair as input and emits a single key and list of corresponding values as output.
It accepts a single key-value pairs as input and can emit only one key-value pair as output.
It accepts a list key-value pairs as input and can emit only one key-value pair as output.
It accepts a single key-value pairs as input and can emit any number of key-value pair as output, including zero.
Which HDFS command copies an HDFS file named foo to the local filesystem as localFoo?
hadoop fs -get foo LocalFoo
hadoop -cp foo LocalFoo
hadoop fs -Is foo
hadoop fs -put foo LocalFoo
Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and generate Java classes to interact with that imported data?
Hortonworks Hadoop-PR000007 Exam (Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer)) Detailed Information
Hadoop-PR000007 Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer)
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Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer) exam
Hortonworks facts Platform 2.0 ships | Hadoop-PR000007 Real Questions and VCE Practice Test
We knew this present day would come. As I said last week, Apache Hadoop 2.0 become launched to accepted availability, and now top Hadoop dealer Hortonworks has replied in kind with the two.0 edition of its personal Hortonworks information Platform (HDP) distribution. considering that Hortonworks architect and co-founder Arun Murthy was on the helm of the Apache Hadoop free up, a prompt replace from Hortonworks was completely expected.
Knitting some YARNThe hallmark of the two.0 releases of Apache Hadoop and HDP is the inclusion YARN -- an acronym for Yet one more useful resource Negotiator -- which components out the management components of Hadoop's MapReduce engine from the MapReduce processing algoritm itself. In different phrases, while Hadoop 2.0 can use MapReduce to procedure information, it's now only 1 of probably many algorithms that can plug into the engine.
when you are trying to find a brief and dirty definition for MapReduce, it's an algorithm that preprocesses records into key and cost pairs in a "Map" step, then aggregates or consolidates that statistics in a "reduce" step, and does this in parallel throughout diverse nodes in a compute cluster.
Stinger, take IIAlong with YARN comes further construction to a Hortonworks-led undertaking called Stinger. Stinger goals to make Apache Hive 100x faster than it had been before the venture all started. Hive is the Apache engine that very nearly converts SQL queries to MapReduce jobs, accordingly enabling standard reporting and BI tools to question Hadoop, albeit a little bit slowly.
part 1 of Stinger (which contains SQL compatibility enhancements, column shop know-how, compression and in-reminiscence hash joins) had already been applied. With the release of HDP, and Hadoop, 2.0, Hive 0.12 and Stinger phase 2 -- where Hive continues to make use of MapReduce however nevertheless merits from YARN working beneath it -- is now being delivered. Hortonworks told me that Stinger section 2 now provides 60x-70x performance improvements over the pre-Stinger releases of Hive, due in massive half to straight Hive improvements, together with vector-based queries and optimizations for thus-referred to as star joins that are typical in information warehouse-type query situations.
Stinger part three will run on an engine referred to as Tez (the Hindi word for "velocity," suggested "taze"), with the intention to swap MapReduce out utterly. And on the grounds that Stinger section 2 has completed the 60x-70x mark already, Hortonworks informed me they felt quite confident that Stinger phase 3 might also well exceed the 100x aim initially set out for the undertaking. it can be mentioned that any Hadoop distro that contains Hadoop 2.0 and Hive 0.12 will include the Stinger section 2 advancements, as the code isn't proprietary to Hortonworks, but a part of the Open source Hive venture.
What's within the boxHDP 2.0 comprises updates throughout the quite a few Hadoop stack components, together with HBase, Pig and, as already outlined, Hive. here figure details the a lot of models of Apache assignment releases covered with various releases of HDP:
HDP versions HDP/Apache edition map
items from a couple of companions, together with Microstrategy, Tableau, Splunk, WANdisco, Talend and Elasticsearch are already HDP 2.0-certified.
The HDP Sandbox, a pre-constructed virtual machine graphic containing the entire HDP setting up, and will be updated for HDP 2.0 presently and will include tutorials from Hortonworks, but also from third parties together with Microsoft, Talend and Tableau.
Hadoop on WindowsSpeaking of Microsoft, the home windows taste of HDP 2.0 will drop in mid-November, in line with Hortonworks. The reason behind the brief lag rests mostly on some finishing touches round integration between Apache Ambari and Microsoft system center. The windows version of the HDP Sandbox, obtainable in VMWare, digital container and Hyper-V digital computer codecs, will be up-to-date as smartly.
The HDP 2.0 unlock is large news...and with Strata/Hadoop World arising subsequent week in new york city, I predict there can be much more very soon.
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