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Cloudera CCA-500 : Cloudera Certified Administrator for Apache Hadoop (CCAH) Exam

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Exam Number : CCA-500
Exam Name : Cloudera Certified Administrator for Apache Hadoop (CCAH)
Vendor Name : Cloudera
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Exam Title : Cloudera Certified Administrator for Apache Hadoop
Exam ID : CCA-500
Number of Questions: 60 questions
Time Limit: 90 minutes
Passing Score: 70%
Language: English, Japanese

1. HDFS (17%)
Describe the function of HDFS daemons
Describe the normal operation of an Apache Hadoop cluster, both in data storage and in data processing
Identify current features of computing systems that motivate a system like Apache Hadoop
Classify major goals of HDFS Design
Given a scenario, identify appropriate use case for HDFS Federation
Identify components and daemon of an HDFS HA-Quorum cluster
Analyze the role of HDFS security (Kerberos)
Determine the best data serialization choice for a given scenario
Describe file read and write paths
Identify the commands to manipulate files in the Hadoop File System Shell
2. YARN (17%)
Understand how to deploy core ecosystem components, including Spark, Impala, and Hive
Understand how to deploy MapReduce v2 (MRv2 / YARN), including all YARN daemons
Understand basic design strategy for YARN and Hadoop
Determine how YARN handles resource allocations
Identify the workflow of job running on YARN
Determine which files you must change and how in order to migrate a cluster from MapReduce version 1 (MRv1) to MapReduce version 2 (MRv2) running on YARN
3. Hadoop Cluster Planning (16%)
Principal points to consider in choosing the hardware and operating systems to host an Apache Hadoop cluster
Analyze the choices in selecting an OS
Understand kernel tuning and disk swapping
Given a scenario and workload pattern, identify a hardware configuration appropriate to the scenario
Given a scenario, determine the ecosystem components your cluster needs to run in order to fulfill the SLA
Cluster sizing: given a scenario and frequency of execution, identify the specifics for the workload, including CPU, memory, storage, disk I/O
Disk Sizing and Configuration, including JBOD versus RAID, SANs, virtualization, and disk sizing requirements in a cluster
Network Topologies: understand network usage in Hadoop (for both HDFS and MapReduce) and propose or identify key network
design components for a given scenario
4. Hadoop Cluster Installation and Administration (25%)
Given a scenario, identify how the cluster will handle disk and machine failures
Analyze a logging configuration and logging configuration file format
Understand the basics of Hadoop metrics and cluster health monitoring
Identify the function and purpose of available tools for cluster monitoring
Be able to install all the ecoystme components in CDH 5, including (but not limited to): Impala, Flume, Oozie, Hue, Cloudera Manager, Sqoop, Hive, and Pig
Identify the function and purpose of available tools for managing the Apache Hadoop file system
5. Resource Management (10%)
Understand the overall design goals of each of Hadoop schedulers
Given a scenario, determine how the FIFO Scheduler allocates cluster resources
Given a scenario, determine how the Fair Scheduler allocates cluster resources under YARN
Given a scenario, determine how the Capacity Scheduler allocates cluster resources
6. Monitoring and Logging (15%)
Understand the functions and features of Hadoops metric collection abilities
Analyze the NameNode and JobTracker Web UIs
Understand how to monitor cluster daemons
Identify and monitor CPU usage on master nodes
Describe how to monitor swap and memory allocation on all nodes
Identify how to view and manage Hadoops log files
Interpret a log file



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Cloudera Hadoop study tips

getting to the basis of your data’s historical past | CCA-500 Cheatsheet and Study Guide

With the rise of massive facts platforms reminiscent of Apache Hadoop and Spark, further and further businesses are pouring commercial enterprise advice into data lakes and launching related initiatives round facts best, records governance, regulatory compliance, and more legit company intelligence (BI). To stay away from the new lakes from changing into swamps, however, businesses are organizing their reams of records by the use of the records’s lineage.

companies have long managed and queried relational records in structured databases and statistics marts.  rising environments comparable to Hadoop, although, regularly collect this advice with semi-structured statistics from NoSQL databases, emails and XML documents in addition to unstructured information like Microsoft workplace files, net pages, videos, audio info, pictures, social media messages, and satellite images.

“despite the fact that statistics is fitting extra attainable, clients still rely on receiving data from trusted interior sources. For a company, it’s critical for users to understand and be aware the source and veracity of the facts. statistics lineage equipment allow groups to music, audit and provide a visible of facts stream from the supply to the target, which also ties into the necessary facts governance tactics,” referred to Sue Clark, senior CTO architect at Sungard AS, a client of Informatica, Teradata, and Qlik.

through new laws like the widely wide-spread statistics insurance policy law (GDPR) and California purchaser privateness Act (CCPA) of 2018, executive regulators are requiring businesses to perform improved management of facts originating from all kinds of raw formats. organisations additionally face expanding calls for from business managers for bigger satisfactory data to be used in predictive evaluation and other BI reviews.

“these days, corporations can’t afford now not to make facts-pushed decisions, which means knowing where facts comes from — and the way it has changed along the manner – to resolve company complications,” in response to Harald Smith, director of product administration, at Syncsort, a professional in data integration application and functions.

“Regulatory compliance calls for accuracy, and information lineage tools assure a tremendously greater accurate method to records administration,” echoed Amnon Drori, founder and CEO  of Octopai, maker of an automated information lineage and metadata administration search engine for BI agencies.

data lineage equipment additionally reveal up in self-service BI solutions, despite the fact curiously, such solutions aren’t yet available to all that many users. in a single contemporary look at, TDWI found that best 20 % of the companies surveyed talked about their personnel might establish trusted records sources on their personal. additional, basically 18 p.c spoke back that personnel could  “assess facts lineage — it truly is, who created the statistics set and the place it came from — devoid of close IT support,” according to the record.

“If clients and analysts are to work without problems with self-carrier BI and analytics, they should be confident that they could find trusted records and recognize its lineage.  For self-carrier to prosper, IT and/or the CDO characteristic need to assist users by way of stewarding their experiences and pointing them to depended on, neatly-governed sources for their analysis,” advised TDWI.

Even fewer of the respondents to TDWI’s survey, or 16 p.c, noted their conclusion users have been capable of query sources similar to Hadoop clusters and statistics lakes – however then once more, best about one-quarter of the collaborating companies even had a data lake.

What are facts lineage tools, anyway?Dozens of proprietary and open-supply providers are converging on information lineage, from a bunch of distinctive instructions. providers, consumers and analysts outline data lineage tools in a wide selection of ways, but Gartner has arrived at one brief yet totally serviceable definition.

“records lineage specifies the facts’s origins and the place it strikes over time. It also describes what occurs to facts because it goes via distinct methods. records lineage can assist to analyze how counsel is used and to song key bits of assistance that serve a selected goal,” in keeping with Gartner’s 2018 Magic Quadrant for Metadata administration options (MMS) report.

Muddying the definitional waters a bit is the indisputable fact that corporations commonly use statistics lineage tools inside sweeping organizational initiatives. therefore, providers regularly integrate these equipment with connected facts management or BI services, either within their personal structures or with partners’ solutions. purchasers also function their personal tool integrations.

Some statistics lineage equipment additionally radically change, or convert, statistics into different formats, however different carriers operate these conversions through separate ETL (extract, transform, load) equipment. Syncsort’s DMX-h, as an instance, accesses information from the mainframe, RDBMS, or different legacy sources and provides security, management, and conclusion-to-end lineage monitoring. It additionally transforms legacy statistics sources into Hadoop-compatible formats.

past comfortably monitoring records, for instance, corporations deserve to be capable of consume the records lineage information in a method that gives them a more robust knowing of what it means, spoke of  Syncsort’s Smith. in consequence, Syncsort lately teamed up with Cloudera to make its lineage suggestions obtainable via Cloudera Navigator, a data governance solution for Hadoop that collects audit logs from across the entire platform and maintains a full heritage, viewable through a graphical consumer interface (GUI) dashboard.

For businesses that don’t use Navigator, DMX-h makes the lineage suggestions purchasable via a rest-API, which IT departments can use for integration with other governance options.

Some perform influence analysisImpact evaluation capabilities are additionally provided in some records lineage tools.  “With the implementation of GDPR, organizations in possession of personal statistics of european residents have had to make gigantic adjustments to make certain compliance. a huge part of this pertains to entry — giving americans entry to their own own records, enabling portability of the information, changing or deleting the facts,” according to Drori.

“before any enterprise can make a transformation to its facts, it have to first locate the statistics after which of route take into account the influence of constructing a selected alternate. statistics lineage equipment are assisting BI agencies to perform have an impact on evaluation forward of compliance with rules like GDPR.”

in one real-world scenario, as an instance, a business analyst mandatory to erase PII, an age column in a selected file, in order that client age would develop into inner most. statistics lineage tools helped to solve the difficulty.

“before erasing a column the analyst needed to consider which approaches have been involved in creating this specific file and what kind of impact the deletion of this age column would have on other reviews. with out statistics lineage tools, have an impact on analysis can also be in reality tricky and sometimes unattainable to function precisely,” he advised SD instances.

the place does information lineage fit?experts slice and cube the data management and BI markets into myriad types of pieces. In characterizing where records lineage tools healthy, most important analyst businesses similar to Gartner and IDC region these equipment within the time-honored classification of metadata administration.

Gartner’s take. beyond equipment for information lineage and influence analysis, items in the metadata administration category can include metadata repositories, or libraries; company glossaries; semantic frameworks; suggestions management tools; and tools for metadata ingestion and translation, in line with Gartner.

equipment within the latter category consist of suggestions and bridges for a variety of information sources similar to ETL; BI and reporting tools; modeling equipment; DBMS catalogs; ERP and different purposes; XML codecs; hardware and network log info; PDF and Microsoft Excel/notice files; enterprise metadata; and customized metadata.

companies who made it into Gartner’s 2018 Magic Quadrant for MMS are as follows: Adaptive, Alation, Alex options, ASG technologies, Collibra, statistics capabilities group, Datum, world IDs, IBM, Infogix, Informatica, Oracle, SAP, and Smartlogic.

“I don’t have accurate adoption charges, but focus of doing appropriate metadata administration is growing. initial resistance at the notion it might take faraway from agility goes away. organizations can actually add new workloads a whole lot faster because the suitable self-discipline is in area,” talked about Sanjeev Mohan, a research analyst for massive records and cloud/SaaS at Gartner, right through an interview with SD times.

agencies, though, have differing explanations for undertaking statistics satisfactory initiatives. earlier than launching an initiative and picking an method to take, an commercial enterprise may still first examine the enterprise use case, he informed.  “Is it regulatory compliance? chance reduction? Predictive evaluation?”

IDC’s views. Stewart Bond, an IDC analyst, classifies metadata administration equipment as belonging to a bigger class, called statistics intelligence application. extra, Bond views data intelligence software as a collection of capabilities which may assist groups reply simple questions about statistics. The checklist of is rather lengthy, however it contains questions on when the records turned into created, who is at present the use of the information, the place it resides, and why it exists, for instance. The answers can inform and e book use situations around facts governance, information exceptional management, and self-provider information, he says.

“To assemble these answers, corporations have to harness the power of metadata it truly is generated each time information is captured at a source, strikes via an organization, is accessed with the aid of users, is profiled, cleansed, aggregated, augmented and used for analytics for operational or strategic choice-making. information intelligence utility goes beyond simply metadata management, and comprises facts cataloging, master records definition and control, facts profiling and statistics stewardship,” Bond wrote in a contemporary blog.

records intelligence is a subset and distinctive view of facts Integration and Integrity software (DIIS), one more market view described by means of IDC, according to Bond, who's analysis director of DIIS at IDC. “statistics intelligence consists of software for statistics profiling and stewardship, grasp records definition and manage, records cataloging and information lineage – all which additionally map into the facts first-rate, metadata management and grasp information segments in the full DIIS market,” Bond told SD instances in an email.

Examples of providers blanketed in IDC’s statistics intelligence and DIIS views are Alation, ASG applied sciences, BackOffice associates, Collibra, Datum, IBM, Infogix, Informatica, Manta, Oracle, SAP, SAS, Syncsort, Tamr, TIBCO, Unifi, and Waterline records.

although, many products containing statistics lineage equipment aren't covered in IDC’s facts intelligence and DIIS views, or in Gartner’s MMS Magic Quadrant, typically as a result of they don’t meet the certain criteria for those categories and are covered by means of other areas of analysts’ agencies.

Which records lineage equipment are top-rated?With so many selections purchasable, which records lineage tools will best meet your needs? elements to trust consist of even if an initiative is IT- or enterprise-pushed, the sorts of extra statistics management or BI performance that will be required, and even if the use of open-source utility is crucial to the organization, experts say.

Some IT-pushed initiatives are concerned with pruning through and curating the corporation’s suggestions into facts catalogs, so that essentially the most accurate records can then be reused through enterprise functions.  different initiatives are sparked by means of enterprise managers in search of to directly put together consistent and reliable facts sets for use inside company departments or company-extensive.

For IT-pushed initiatives, for example, Informatica gives records lineage through Metadata supervisor, a key part of Informatica vigour core superior version. Metadata supervisor gathers technical metadata from sources equivalent to ETL and BI tools, applications, databases, facts modeling tools, and mainframes.

Metadata manager shares a principal repository with Informatica’s business thesaurus. The technical metadata can be linked to business metadata created by using company thesaurus so as to add context and desiring to data integration. Metadata supervisor also gives a graphical view of the records because it strikes in the course of the integration atmosphere.

IT developers can use Metadata supervisor to function have an effect on analysis when alterations are made to metadata.  business facts architects can use the answer’s integration metadata catalog for applications akin to browsing and searching for metadata definitions, defining new customized models, and maintaining ordinary interface definitions for data sources, warehouses, BI, and different functions utilized in commercial enterprise data integration initiatives.

In stark contrast, Datawatch targets its Monarch platform at business-pushed initiatives. Monarch allows for domain certified in company departments to pull metadata for files in multiple codecs – reminiscent of Excel spreadsheets, Oracle RDMS, and Salesforce.com, as an instance — and then use the metadata to build dashboard-pushed fashions for reuse within their departments, talked about Jon Pilkington, Datawatch’s CPO, in an interview with SD times.

Monarch’s data lineage tools document “the place the uncooked facts got here from, how it’s been altered, who did it, after they did it,” for example. “The model then becomes what users search for and store,” Pilkington remarked.

Monarch extracts the raw information in rows and columns. After it’s extracted, a domain expert uses Monarch’s element-and-click on consumer interface to transform, clean, blend and enrich facts devoid of performing any coding or scripting. it could actually then be analyzed without delay inside Monarch or exported to Excel spreadsheets or third-party superior analytics and visualization equipment through the use of developed-in connectors.

within its personal advertising and marketing branch, for instance, Datawatch has used its equipment to generate reports by using salespeople about how information turns right into a sales lead and how lengthy it takes to turn a lead into a sale. “We use 11 diverse facts sources for this – together with Google advert phrases and the Zendesk guide gadget – and the apps don’t always play neatly together. It took many steps for the domain skilled to get the suggestions into form, however now that the mannequin is executed, it can be reused by using any salesperson in the branch.”

Three procedures to facts managementAs Gartner’s Sanjeev Mohan sees it, businesses can take any of three approaches to statistics management initiatives:  customer-developed, mixing and matching optimum-of-breed tools, and investing in a broader platform or suite.

through opting for a most reliable-of-breed facts lineage tool or metadata administration kit, a customer can obtain strong support for a selected use-case situation, the analyst accompanied. having said that, shoppers frequently should operate their own device integrations, a method that can also be expensive and time-ingesting.

Sungard AS is one instance of an business which is taking a ideal-of-breed strategy. “As part of its inner coping with of records and its sources, Sungard AS makes use of Teradata and Informatica, with Qlik on appropriate of Teradata for ease of business consumer access and to make facts-backed business decisions easier.” Sungard’s Sue Clark told SD instances.

Open source vs. proprietary. Most options providing information lineage capabilities are proprietary, observed Gartner’s Mohan. Yet some are open supply, together with choices from Hortonworks, Cloudera, MapR and the now Google-owned Cask facts, besides Teradata’s Kylo.

“We don’t like to lock shoppers into a particular seller,” talked about Shaun Bierweiler, vice chairman of U.S. Public Sector at Hortonworks, in an interview with SD instances.

Hortonworks is now working with the U.S. Census Bureau to provide know-how for the 2020 census, the first countrywide census to be performed in a certainly digital approach. HDP will serve as the Census data Lake, storing most of the census information, whereas also acting as a staging ground for joining data from other databases. The Census Lake will keep both structured facts moreover unstructured facts reminiscent of road-level and aerial map imagery from Google.




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