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Cloudera CCP DE575 Data Engineer
Hadoop Certification material. Total 79
Solved
scenarios which
includes
in depth complex scenarios solved for Sqoop, flume,
Hive,Avro,HDFS, OOzie workflow linear, branch, decision,
scheduled, coordinator and regular expressions based
questions and many more.
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can be solved mixing the components e.g. Hive and Sqoop ,
flume and HIve, OOzie and Hive etc. We have added complex
scenerio as well as step by step solutions and each
solution is executed by our technical team to make sure it
works perfectly. This
problem scnerios not only helps for CCP DE575 Data
Engineer exam, but also it will help in becoming Data
Engineer using Hadoop eco-system. You can solve similar
problems in your daily job. Hence solve these scenarios
and become BigData experts, with HandsOn. Once
you complete all 73 problem scenarios your own, you will
be ready to clear real CCP DE575 exam. This is the one of
the most demanding certification among the Hadoop Data
Engineer on HadoopExam.com . Technical team is working to
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Features of the
CCP DE:575 (Cloudera Hadoop and Spark Developer certification)
1. Entire syllabus will be covered.
2. All questions are scenerio based and step by step solutions will be
given
3. Same will be executed by our exper technical team and
complimentary selected
recorded
videos will
be shared
here.
(In progress)
4. Almost all scenerios will be covered for real exams.
5. Any future updates will be free on single and same machine.
6. Solutions are already executed on Cloudera CDH, hence same can be used
for real exam.
7. Our expert regularly update the simulator.
8. It will help you gain confidence and reduce study time.
9. Always updated and correct/incorrect way of solutions explanation
Note : This product is tested only on
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Syllabus for CCP:DE575 (Data
Engineer)
Data Ingest
The skills to transfer data between external systems and your cluster.
This includes the following:
- Import and export data between an external RDBMS and your cluster,
including the ability to import specific subsets, change the delimiter
and file format of imported data during ingest, and alter the data
access pattern or privileges.
- Ingest real-time and near-real time (NRT) streaming data into HDFS,
including the ability to distribute to multiple data sources and
convert data on ingest from one format to another.
- Load data into and out of HDFS using the Hadoop File System (FS)
commands.
Transform,
Stage, Store
Convert a set of data values in a given format stored in HDFS into new
data values and/or a new data format and write them into HDFS or
Hive/HCatalog. This includes the following skills:
- Convert data from one file format to another
- Write your data with compression
- Convert data from one set of values to another (e.g., Lat/Long to
Postal Address using an external library)
- Change the data format of values in a data set
- Purge bad records from a data set, e.g., null values
- Deduplication and merge data
- Denormalize data from multiple disparate data sets
- Evolve an Avro or Parquet schema
- Partition an existing data set according to one or more partition
keys
- Tune data for optimal query performance
Data Analysis
Filter, sort, join, aggregate, and/or transform one or more data sets in a
given format stored in HDFS to produce a specified result. All of these
tasks may include reading from Parquet, Avro, JSON, delimited text, and
natural language text. The queries will include complex data types (e.g.,
array, map, struct), the implementation of external libraries, partitioned
data, compressed data, and require the use of metadata from Hive/HCatalog.
- Write a query to aggregate multiple rows of data
- Write a query to calculate aggregate statistics (e.g., average or
sum)
- Write a query to filter data
- Write a query that produces ranked or sorted data
- Write a query that joins multiple data sets
- Read and/or create a Hive or an HCatalog table from existing data in
HDFS
Workflow
The ability to create and execute various jobs and actions that move data
towards greater value and use in a system. This includes the following
skills:
- Create and execute a linear workflow with actions that include
Hadoop jobs, Hive jobs, Pig jobs, custom actions, etc.
- Create and execute a branching workflow with actions that include
Hadoop jobs, Hive jobs, Pig jobs, custom action, etc.
- Orchestrate a workflow to execute regularly at predefined times,
including workflows that have data dependencies
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