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CCA175 CCA Spark and Hadoop Developer

Exam Detail:
The CCA175 (CCA Spark and Hadoop Developer) is a certification exam that validates the skills and knowledge of individuals in developing and deploying Spark and Hadoop applications. Here are the exam details for CCA175:

- Number of Questions: The exam typically consists of multiple-choice and hands-on coding questions. The exact number of questions may vary, but typically, the exam includes around 8 to 12 tasks that require coding and data manipulation.

- Time Limit: The time allocated to complete the exam is 120 minutes (2 hours).

Course Outline:
The CCA175 course covers various syllabus related to Apache Spark, Hadoop, and data processing. The course outline typically includes the following topics:

1. Introduction to Big Data and Hadoop:
- Overview of Big Data concepts and challenges.
- Introduction to Hadoop and its ecosystem components.

2. Hadoop File System (HDFS):
- Understanding Hadoop Distributed File System (HDFS).
- Managing and manipulating data in HDFS.
- Performing file system operations using Hadoop commands.

3. Apache Spark Fundamentals:
- Introduction to Apache Spark and its features.
- Understanding Spark architecture and execution model.
- Writing and running Spark applications using Spark Shell.

4. Spark Data Processing:
- Transforming and manipulating data using Spark RDDs (Resilient Distributed Datasets).
- Applying transformations and actions to RDDs.
- Working with Spark DataFrames and Datasets.

5. Spark SQL and Data Analysis:
- Querying and analyzing data using Spark SQL.
- Performing data aggregation, filtering, and sorting operations.
- Working with structured and semi-structured data.

6. Spark Streaming and Data Integration:
- Processing real-time data using Spark Streaming.
- Integrating Spark with external data sources and systems.
- Handling data ingestion and data integration challenges.

Exam Objectives:
The objectives of the CCA175 exam are as follows:

- Evaluating candidates' knowledge of Hadoop ecosystem components and their usage.
- Assessing candidates' proficiency in coding Spark applications using Scala or Python.
- Testing candidates' ability to manipulate and process data using Spark RDDs, DataFrames, and Spark SQL.
- Assessing candidates' understanding of data integration and streaming concepts in Spark.

Exam Syllabus:
The specific exam syllabus for the CCA175 exam covers the following areas:

1. Data Ingestion: Ingesting data into Hadoop using various techniques (e.g., Sqoop, Flume).

2. Transforming Data with Apache Spark: Transforming and manipulating data using Spark RDDs, DataFrames, and Spark SQL.

3. Loading Data into Hadoop: Loading data into Hadoop using various techniques (e.g., Sqoop, Flume).

4. Querying Data with Apache Hive: Querying data stored in Hadoop using Apache Hive.

5. Data Analysis with Apache Spark: Analyzing and processing data using Spark RDDs, DataFrames, and Spark SQL.

6. Writing Spark Applications: Writing and executing Spark applications using Scala or Python.
CCA Spark and Hadoop Developer
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CCA175 CCA Spark and Hadoop Developer

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Question: 94
Now import the data from following directory into departments_export table, /user/cloudera/departments new
Answer: Solution:
Step 1: Login to musql db
mysql user=retail_dba -password=cloudera
show databases; use retail_db; show tables;
step 2: Create a table as given in problem statement.
CREATE table departments_export (departmentjd int(11), department_name varchar(45), created_date T1MESTAMP
DEFAULT NOW());
show tables;
Step 3: Export data from /user/cloudera/departmentsnew to new table departments_export
sqoop export -connect jdbc:mysql://quickstart:3306/retail_db
-username retaildba
password cloudera
table departments_export
-export-dir /user/cloudera/departments_new
-batch
Step 4: Now check the export is correctly done or not. mysql -user*retail_dba -password=cloudera
show databases;
use retail _db;
show tables;
select from departments_export;
Question: 95
Data should be written as text to hdfs
Answer: Solution:
Step 1: Create directory mkdir /tmp/spooldir2
Step 2: Create flume configuration file, with below configuration for source, sink and channel and save it in
flume8.conf.
agent1 .sources = source1
agent1.sinks = sink1a sink1b agent1.channels = channel1a channel1b
agent1.sources.source1.channels = channel1a channel1b
agent1.sources.source1.selector.type = replicating
agent1.sources.source1.selector.optional = channel1b
agent1.sinks.sink1a.channel = channel1a
agent1 .sinks.sink1b.channel = channel1b
agent1.sources.source1.type = spooldir
agent1 .sources.sourcel.spoolDir = /tmp/spooldir2
agent1.sinks.sink1a.type = hdfs
agent1 .sinks, sink1a.hdfs. path = /tmp/flume/primary
agent1 .sinks.sink1a.hdfs.tilePrefix = events
agent1 .sinks.sink1a.hdfs.fileSuffix = .log
agent1 .sinks.sink1a.hdfs.fileType = Data Stream
agent1 . sinks.sink1b.type = hdfs
agent1 . sinks.sink1b.hdfs.path = /tmp/flume/secondary
agent1 .sinks.sink1b.hdfs.filePrefix = events
agent1.sinks.sink1b.hdfs.fileSuffix = .log
agent1 .sinks.sink1b.hdfs.fileType = Data Stream
agent1.channels.channel1a.type = file
agent1.channels.channel1b.type = memory
step 4: Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flume8.conf name age
Step 5: Open another terminal and create a file in /tmp/spooldir2/
echo "IBM, 100, 20160104" /tmp/spooldir2/.bb.txt
echo "IBM, 103, 20160105" /tmp/spooldir2/.bb.txt mv /tmp/spooldir2/.bb.txt /tmp/spooldir2/bb.txt
After few mins
echo "IBM.100.2, 20160104" /tmp/spooldir2/.dr.txt
echo "IBM, 103.1, 20160105" /tmp/spooldir2/.dr.txt mv /tmp/spooldir2/.dr.txt /tmp/spooldir2/dr.txt
Question: 96
Data should be written as text to hdfs
Answer: Solution:
Step 1: Create directory mkdir /tmp/spooldir/bb mkdir /tmp/spooldir/dr
Step 2: Create flume configuration file, with below configuration for
agent1.sources = source1 source2
agent1 .sinks = sink1
agent1.channels = channel1
agent1 .sources.source1.channels = channel1
agentl .sources.source2.channels = channell agent1 .sinks.sinkl.channel = channell
agent1 . sources.source1.type = spooldir
agent1 .sources.sourcel.spoolDir = /tmp/spooldir/bb
agent1 . sources.source2.type = spooldir
agent1 .sources.source2.spoolDir = /tmp/spooldir/dr
agent1 . sinks.sink1.type = hdfs
agent1 .sinks.sink1.hdfs.path = /tmp/flume/finance
agent1-sinks.sink1.hdfs.filePrefix = events
agent1.sinks.sink1.hdfs.fileSuffix = .log
agent1 .sinks.sink1.hdfs.inUsePrefix = _
agent1 .sinks.sink1.hdfs.fileType = Data Stream
agent1.channels.channel1.type = file
Step 4: Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/fIumeconf/fIume7.conf name agent1
Step 5: Open another terminal and create a file in /tmp/spooldir/
echo "IBM, 100, 20160104" /tmp/spooldir/bb/.bb.txt
echo "IBM, 103, 20160105" /tmp/spooldir/bb/.bb.txt mv /tmp/spooldir/bb/.bb.txt /tmp/spooldir/bb/bb.txt
After few mins
echo "IBM, 100.2, 20160104" /tmp/spooldir/dr/.dr.txt
echo "IBM, 103.1, 20160105" /tmp/spooldir/dr/.dr.txt mv /tmp/spooldir/dr/.dr.txt /tmp/spooldir/dr/dr.txt
Question: 97
Data should be written as text to hdfs
Answer: Solution:
Step 1: Create directory mkdir /tmp/spooldir2
Step 2: Create flume configuration file, with below configuration for source, sink and channel and save it in
flume8.conf.
agent1 .sources = source1
agent1.sinks = sink1a sink1b agent1.channels = channel1a channel1b
agent1.sources.source1.channels = channel1a channel1b
agent1.sources.source1.selector.type = replicating
agent1.sources.source1.selector.optional = channel1b
agent1.sinks.sink1a.channel = channel1a
agent1 .sinks.sink1b.channel = channel1b
agent1.sources.source1.type = spooldir
agent1 .sources.sourcel.spoolDir = /tmp/spooldir2
agent1.sinks.sink1a.type = hdfs
agent1 .sinks, sink1a.hdfs. path = /tmp/flume/primary
agent1 .sinks.sink1a.hdfs.tilePrefix = events
agent1 .sinks.sink1a.hdfs.fileSuffix = .log
agent1 .sinks.sink1a.hdfs.fileType = Data Stream
agent1 . sinks.sink1b.type = hdfs
agent1 . sinks.sink1b.hdfs.path = /tmp/flume/secondary
agent1 .sinks.sink1b.hdfs.filePrefix = events
agent1.sinks.sink1b.hdfs.fileSuffix = .log
agent1 .sinks.sink1b.hdfs.fileType = Data Stream
agent1.channels.channel1a.type = file
agent1.channels.channel1b.type = memory
step 4: Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flume8.conf name age
Step 5: Open another terminal and create a file in /tmp/spooldir2/
echo "IBM, 100, 20160104" /tmp/spooldir2/.bb.txt
echo "IBM, 103, 20160105" /tmp/spooldir2/.bb.txt mv /tmp/spooldir2/.bb.txt /tmp/spooldir2/bb.txt
After few mins
echo "IBM.100.2, 20160104" /tmp/spooldir2/.dr.txt
echo "IBM, 103.1, 20160105" /tmp/spooldir2/.dr.txt mv /tmp/spooldir2/.dr.txt /tmp/spooldir2/dr.txt
Question: 98
Data should be written as text to hdfs
Answer: Solution:
Step 1: Create directory mkdir /tmp/nrtcontent
Step 2: Create flume configuration file, with below configuration for source, sink and channel and save it in
flume6.conf.
agent1 .sources = source1
agent1 .sinks = sink1
agent1.channels = channel1
agent1 .sources.source1.channels = channel1
agent1 .sinks.sink1.channel = channel1
agent1 . sources.source1.type = spooldir
agent1 .sources.source1.spoolDir = /tmp/nrtcontent
agent1 .sinks.sink1 .type = hdfs
agent1 . sinks.sink1.hdfs .path = /tmp/flume
agent1.sinks.sink1.hdfs.filePrefix = events
agent1.sinks.sink1.hdfs.fileSuffix = .log
agent1 .sinks.sink1.hdfs.inUsePrefix = _
agent1 .sinks.sink1.hdfs.fileType = Data Stream
Step 4: Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/fIumeconf/fIume6.conf name agent1
Step 5: Open another terminal and create a file in /tmp/nrtcontent
echo "I am preparing for CCA175 from ABCTech m.com " > /tmp/nrtcontent/.he1.txt
mv /tmp/nrtcontent/.he1.txt /tmp/nrtcontent/he1.txt
After few mins
echo "I am preparing for CCA175 from TopTech .com " > /tmp/nrtcontent/.qt1.txt
mv /tmp/nrtcontent/.qt1.txt /tmp/nrtcontent/qt1.txt
Question: 99
Problem Scenario 4: You have been given MySQL DB with following details.
user=retail_dba
password=cloudera
database=retail_db
table=retail_db.categories
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following activities.
Import Single table categories (Subset data} to hive managed table, where category_id between 1 and 22
Answer: Solution:
Step 1: Import Single table (Subset data)
sqoop import connect jdbc:mysql://quickstart:3306/retail_db -username=retail_dba -password=cloudera -
table=categories -where " category_id between 1 and 22" hive-import m 1
Note: Here the is the same you find on ~ key
This command will create a managed table and content will be created in the following directory.
/user/hive/warehouse/categories
Step 2: Check whether table is created or not (In Hive)
show tables;
select * from categories;
Question: 100
Data should be written as text to hdfs
Answer: Solution:
Step 1: Create directory mkdir /tmp/spooldir/bb mkdir /tmp/spooldir/dr
Step 2: Create flume configuration file, with below configuration for
agent1.sources = source1 source2
agent1 .sinks = sink1
agent1.channels = channel1
agent1 .sources.source1.channels = channel1
agentl .sources.source2.channels = channell agent1 .sinks.sinkl.channel = channell
agent1 . sources.source1.type = spooldir
agent1 .sources.sourcel.spoolDir = /tmp/spooldir/bb
agent1 . sources.source2.type = spooldir
agent1 .sources.source2.spoolDir = /tmp/spooldir/dr
agent1 . sinks.sink1.type = hdfs
agent1 .sinks.sink1.hdfs.path = /tmp/flume/finance
agent1-sinks.sink1.hdfs.filePrefix = events
agent1.sinks.sink1.hdfs.fileSuffix = .log
agent1 .sinks.sink1.hdfs.inUsePrefix = _
agent1 .sinks.sink1.hdfs.fileType = Data Stream
agent1.channels.channel1.type = file
Step 4: Run below command which will use this configuration file and append data in hdfs.
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/fIumeconf/fIume7.conf name agent1
Step 5: Open another terminal and create a file in /tmp/spooldir/
echo "IBM, 100, 20160104" /tmp/spooldir/bb/.bb.txt
echo "IBM, 103, 20160105" /tmp/spooldir/bb/.bb.txt mv /tmp/spooldir/bb/.bb.txt /tmp/spooldir/bb/bb.txt
After few mins
echo "IBM, 100.2, 20160104" /tmp/spooldir/dr/.dr.txt
echo "IBM, 103.1, 20160105" /tmp/spooldir/dr/.dr.txt mv /tmp/spooldir/dr/.dr.txt /tmp/spooldir/dr/dr.txt
Question: 101
Problem Scenario 21: You have been given log generating service as below.
startjogs (It will generate continuous logs)
tailjogs (You can check, what logs are being generated)
stopjogs (It will stop the log service)
Path where logs are generated using above service: /opt/gen_logs/logs/access.log
Now write a flume configuration file named flumel.conf, using that configuration file dumps logs in HDFS file system
in a directory called flumel. Flume channel should have following property as well. After every 100 message it should
be committed, use non-durable/faster channel and it should be able to hold maximum 1000 events
Answer: Solution:
Step 1: Create flume configuration file, with below configuration for source, sink and channel.
#Define source, sink, channel and agent,
agent1. sources = source1
agent1 .sinks = sink1
agent1.channels = channel1
# Describe/configure source1
agent1 . sources.source1.type = exec
agent1.sources.source1.command = tail -F /opt/gen logs/logs/access.log
## Describe sinkl
agentl .sinks.sinkl.channel = memory-channel
agentl .sinks.sinkl .type = hdfs
agentl . sinks.sink1.hdfs.path = flumel
agentl .sinks.sinkl.hdfs.fileType = Data Stream
# Now we need to define channell property.
agent1.channels.channel1.type = memory
agent1.channels.channell.capacity = 1000
agent1.channels.channell.transactionCapacity = 100
# Bind the source and sink to the channel
agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1
Step 2: Run below command which will use this configuration file and append data in hdfs.
Start log service using: startjogs
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flumel.conf-
Dflume.root.logger=DEBUG, INFO, console
Wait for few mins and than stop log service.
Stop_logs
Question: 102
Problem Scenario 23: You have been given log generating service as below.
Start_logs (It will generate continuous logs)
Tail_logs (You can check, what logs are being generated)
Stop_logs (It will stop the log service)
Path where logs are generated using above service: /opt/gen_logs/logs/access.log
Now write a flume configuration file named flume3.conf, using that configuration file dumps logs in HDFS file system
in a directory called flumeflume3/%Y/%m/%d/%H/%M
Means every minute new directory should be created). Please us the interceptors to provide timestamp information, if
message header does not have header info.
And also note that you have to preserve existing timestamp, if message contains it. Flume channel should have
following property as well. After every 100 message it should be committed, use non-durable/faster channel and it
should be able to hold maximum 1000 events.
Answer: Solution:
Step 1: Create flume configuration file, with below configuration for source, sink and channel.
#Define source, sink, channel and agent,
agent1 .sources = source1
agent1 .sinks = sink1
agent1.channels = channel1
# Describe/configure source1
agent1 . sources.source1.type = exec
agentl.sources.source1.command = tail -F /opt/gen logs/logs/access.log
#Define interceptors
agent1 .sources.source1.interceptors=i1
agent1 .sources.source1.interceptors.i1.type=timestamp
agent1 .sources.source1.interceptors.i1.preserveExisting=true
## Describe sink1
agent1 .sinks.sink1.channel = memory-channel
agent1 . sinks.sink1.type = hdfs
agent1 . sinks.sink1.hdfs.path = flume3/%Y/%m/%d/%H/%M
agent1 .sinks.sjnkl.hdfs.fileType = Data Stream
# Now we need to define channel1 property.
agent1.channels.channel1.type = memory
agent1.channels.channel1.capacity = 1000
agent1.channels.channel1.transactionCapacity = 100
# Bind the source and sink to the channel
Agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1
Step 2: Run below command which will use this configuration file and append data in hdfs.
Start log service using: start_logs
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flume3.conf -
DfIume.root.logger=DEBUG, INFO, console Cname agent1
Wait for few mins and than stop log service.
stop logs
Question: 103
Problem Scenario 21: You have been given log generating service as below.
startjogs (It will generate continuous logs)
tailjogs (You can check, what logs are being generated)
stopjogs (It will stop the log service)
Path where logs are generated using above service: /opt/gen_logs/logs/access.log
Now write a flume configuration file named flumel.conf, using that configuration file dumps logs in HDFS file system
in a directory called flumel. Flume channel should have following property as well. After every 100 message it should
be committed, use non-durable/faster channel and it should be able to hold maximum 1000 events
Answer: Solution:
Step 1: Create flume configuration file, with below configuration for source, sink and channel.
#Define source, sink, channel and agent,
agent1. sources = source1
agent1 .sinks = sink1
agent1.channels = channel1
# Describe/configure source1
agent1 . sources.source1.type = exec
agent1.sources.source1.command = tail -F /opt/gen logs/logs/access.log
## Describe sinkl
agentl .sinks.sinkl.channel = memory-channel
agentl .sinks.sinkl .type = hdfs
agentl . sinks.sink1.hdfs.path = flumel
agentl .sinks.sinkl.hdfs.fileType = Data Stream
# Now we need to define channell property.
agent1.channels.channel1.type = memory
agent1.channels.channell.capacity = 1000
agent1.channels.channell.transactionCapacity = 100
# Bind the source and sink to the channel
agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1
Step 2: Run below command which will use this configuration file and append data in hdfs.
Start log service using: startjogs
Start flume service:
flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/flumeconf/flumel.conf-
Dflume.root.logger=DEBUG, INFO, console
Wait for few mins and than stop log service.
Stop_logs
Question: 104
Now import data from mysql table departments to this hive table. Please make sure that data should be visible using
below hive command, select" from departments_hive
Answer: Solution:
Step 1: Create hive table as said.
hive
show tables;
create table departments_hive(department_id int, department_name string);
Step 2: The important here is, when we create a table without delimiter fields. Then default delimiter for hive is ^A
(01). Hence, while importing data we have to provide proper delimiter.
sqoop import
-connect jdbc:mysql://quickstart:3306/retail_db
~username=retail_dba
-password=cloudera
table departments
hive-home /user/hive/warehouse
-hive-import
-hive-overwrite
hive-table departments_hive
fields-terminated-by 01
Step 3: Check-the data in directory.
hdfs dfs -Is /user/hive/warehouse/departments_hive
hdfs dfs -cat/user/hive/warehouse/departmentshive/part
Check data in hive table.
Select * from departments_hive;
Question: 105
Import departments table as a text file in /user/cloudera/departments.
Answer: Solution:
Step 1: List tables using sqoop
sqoop list-tables connect jdbc:mysql://quickstart:330G/retail_db username retail dba -password cloudera
Step 2: Eval command, just run a count query on one of the table.
sqoop eval
connect jdbc:mysql://quickstart:3306/retail_db
-username retail_dba
-password cloudera
query "select count(1) from ordeMtems"
Step 3: Import all the tables as avro file.
sqoop import-all-tables
-connect jdbc:mysql://quickstart:3306/retail_db
-username=retail_dba
-password=cloudera
-as-avrodatafile
-warehouse-dir=/user/hive/warehouse/retail stage.db
-ml
Step 4: Import departments table as a text file in /user/cloudera/departments
sqoop import
-connect jdbc:mysql://quickstart:3306/retail_db
-username=retail_dba
-password=cloudera
-table departments
-as-textfile
-target-dir=/user/cloudera/departments
Step 5: Verify the imported data.
hdfs dfs -Is /user/cloudera/departments
hdfs dfs -Is /user/hive/warehouse/retailstage.db
hdfs dfs -Is /user/hive/warehouse/retail_stage.db/products
Question: 106
Problem Scenario 2:
There is a parent organization called "ABC Group Inc", which has two child companies named Tech Inc and MPTech.
Both companies employee information is given in two separate text file as below. Please do the following activity for
employee details.
Tech Inc.txt
Answer: Solution:
Step 1: Check All Available command hdfs dfs
Step 2: Get help on Individual command hdfs dfs -help get
Step 3: Create a directory in HDFS using named Employee and create a Dummy file in it called e.g. Techinc.txt hdfs
dfs -mkdir Employee
Now create an emplty file in Employee directory using Hue.
Step 4: Create a directory on Local file System and then Create two files, with the given data in problems.
Step 5: Now we have an existing directory with content in it, now using HDFS command line, overrid this existing
Employee directory. While copying these files from local file System to HDFS. cd /home/cloudera/Desktop/ hdfs dfs -
put -f Employee
Step 6: Check All files in directory copied successfully hdfs dfs -Is Employee
Step 7: Now merge all the files in Employee directory, hdfs dfs -getmerge -nl Employee MergedEmployee.txt
Step 8: Check the content of the file. cat MergedEmployee.txt
Step 9: Copy merged file in Employeed directory from local file ssytem to HDFS. hdfs dfs -put MergedEmployee.txt
Employee/
Step 10: Check file copied or not. hdfs dfs -Is Employee
Step 11: Change the permission of the merged file on HDFS hdfs dfs -chmpd 664 Employee/MergedEmployee.txt
Step 12: Get the file from HDFS to local file system, hdfs dfs -get Employee Employee_hdfs
Question: 107
Problem Scenario 30: You have been given three csv files in hdfs as below.
EmployeeName.csv with the field (id, name)
EmployeeManager.csv (id, manager Name)
EmployeeSalary.csv (id, Salary)
Using Spark and its API you have to generate a joined output as below and save as a text tile (Separated by comma)
for final distribution and output must be sorted by id.
ld, name, salary, managerName
EmployeeManager.csv
E01, Vishnu
E02, Satyam
E03, Shiv
E04, Sundar
E05, John
E06, Pallavi
E07, Tanvir
E08, Shekhar
E09, Vinod
E10, Jitendra
EmployeeName.csv
E01, Lokesh
E02, Bhupesh
E03, Amit
E04, Ratan
E05, Dinesh
E06, Pavan
E07, Tejas
E08, Sheela
E09, Kumar
E10, Venkat
EmployeeSalary.csv
E01, 50000
E02, 50000
E03, 45000
E04, 45000
E05, 50000
E06, 45000
E07, 50000
E08, 10000
E09, 10000
E10, 10000
Answer: Solution:
Step 1: Create all three files in hdfs in directory called sparkl (We will do using Hue}. However, you can first create in
local filesystem and then
Step 2: Load EmployeeManager.csv file from hdfs and create PairRDDs
val manager = sc.textFile("spark1/EmployeeManager.csv")
val managerPairRDD = manager.map(x=> (x.split(", ")(0), x.split(", ")(1)))
Step 3: Load EmployeeName.csv file from hdfs and create PairRDDs
val name = sc.textFile("spark1/EmployeeName.csv")
val namePairRDD = name.map(x=> (x.split(", ")(0), x.split(")(1)))
Step 4: Load EmployeeSalary.csv file from hdfs and create PairRDDs
val salary = sc.textFile("spark1/EmployeeSalary.csv")
val salaryPairRDD = salary.map(x=> (x.split(", ")(0), x.split(", ")(1)))
Step 4: Join all pairRDDS
val joined = namePairRDD.join(salaryPairRDD}.join(managerPairRDD}
Step 5: Now sort the joined results, val joinedData = joined.sortByKey()
Step 6: Now generate comma separated data.
val finalData = joinedData.map(v=> (v._1, v._2._1._1, v._2._1._2, v._2._2))
Step 7: Save this output in hdfs as text file.
finalData.saveAsTextFile("spark1/result.txt")
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Cloudera Developer information source - BingNews https://killexams.com/pass4sure/exam-detail/CCA175 Search results Cloudera Developer information source - BingNews https://killexams.com/pass4sure/exam-detail/CCA175 https://killexams.com/exam_list/Cloudera Cloudera Packages Hadoop For Enterprise Implementation

Cloudera is packaging its distribution of the open-source Hadoop software with developer tools, technical support, training programs, and sales and marketing resources to make it easier for enterprises to adopt the technology, said Kirk Dunn, COO of the Palo Alto, Calif.-based company.

"We want to help data-driven enterprises who use data as a critical part of their business to use Hadoop," Dunn said.

The Apache Hadoop project is a framework for running applications on large clusters built using commodity hardware. Hadoop works by breaking an application into multiple small fragments of work, each of which may be executed or re-executed on any node in the cluster.

It includes the Hadoop Distributed File System (HDFS) for reliably storing and analyzing very large files across machines in a large cluster

While Hadoop is often tied with cloud technologies for analyzing large amounts of data, it is just as likely to be found in use by enterprises looking for ways to better manage their own data stores, Dunn said. For instance, he said, cloud providers like Yahoo, Amazon, and Twitter all use Hadoop internally for their own data.

"Enterprises don't have the volume of data that Web companies have," he said. "But Web companies don't have the diversity of data sources that enterprises have."

Cloudera has figured out how to package Hadoop for the enterprise, which Dunn said is no trivial matter. While Cloudera's Distribution including Apache Hadoop (CDH) is, like all open source software, available for downloading at no charge, the company is offering it as a package to hardware vendors, ISV, and systems integrators, he said.

Cloudera's new hardware partners include Dell, Cisco, Fujitsu, SGI, and Mellanox, while ISV partners include Informatica, Microstrategy, Teradata, and IBM. Cloudera will also offer its package to both regional or boutique integrators as well as larger, national integrators, Dunn said.

"We're creating an ecosystem where hardware and software vendors and system integrators can come together to look at how to use Hadoop to get better insights into data," he said. "We believe that if we can do that, we can enable Hadoop, which is already growing fast, to get even faster adoption."

Hadoop has received much industry support in the last few months especially as businesses grow more interested in new ways to handle "big data," or data which scales to multiple petabytes of capacity and is created or collected, is stored, and is collaborative in real time.

EMC in May unveiled plans to provide full open-source support for Hadoop with the eventual release of software, appliance, and eventually virtual appliance versions of the Hadoop technology in connection with technology it got with last year's Greenplum acquisition.

That same month, NetApp unveiled a new Hadoop storage appliance based on the E5400 storage subsystem it received with its acquisition of Engenio.

Startup server technology developer Calxeda in June unveiled a group of integrator and ISV partners are developing applications around its upcoming ARM processor-based, power-efficient server technology for use in such applications as Hadoop.

Data integration software vendor Informatica in June released a new version of its flagship product designed to handle the "big data" generated by today's transaction processing and social media systems which also supports Hadoop.

Sun, 10 Dec 2023 02:23:00 -0600 text/html https://www.crn.com/news/storage/231400016/cloudera-packages-hadoop-for-enterprise-implementation
How Broad Is Your Database’s Data Ecosystem? Gartner Takes a Look

(TimeStopper69/Shutterstock)

The days of databases existing as islands unto themselves are over, according to Gartner, which reports the existence of a strong and growing signal for cloud databases to become part of “broader data ecosystems.” Last month, the analyst group rated the ecosystem participation of the top databases, and the results might surprise you.

In mid-December, Gartner released its 2023 Magic Quadrant for Cloud DBMS (CDBMS), which analyzed the market for transactional and analytical databases running in public and private clouds. Nineteen cloud DBMS vendors made the final cut for the quadrant, which was dominated by the likes of AWS, Microsoft Azure, Google Cloud, and Oracle.

A major trend identified by the Gartner analysts is the co-mingling of standard database features and capabilities with the features and capabilities offered in the broader market for data management tools, which have traditionally resided outside of the DBMS proper.

In the past, database customers usually turned to independent software vendors (ISVs) for data management functions like data lineage tracking, data governance, data integration/ETL, data quality, and data security. Many of these functions have been conglomerated into so-called data fabrics, which ensure a measure of repeatability and consistency in various data management processes.

2023 Magic Quadrant for Cloud DBMS (Source: Gartner)

But according to Gartner’s analysts, database vendors are now reaching out and working more closely with the data management ISVs, and vice versa. As the most important layer in the data stack, it’s great that databases are playing nicely (or playing nicer, anyway) with the array of other important data management products that companies must rely upon to get value from data while minimizing cost and risk.

While not all DBMS providers are working with ISVs in the same degree or manner, there’s a clear trend toward DBMSs playing in the data ecosystem, according to Gartner.

“Cloud DBMS systems are already beginning to be aware of, and collaborate with, the other data management components around them,” Gartner writes. “This does not mean that the cloud DBMS systems will subsume the functions of those other systems; rather, they will be aware of them and add more value by interoperating with them.”

There has been “a major improvement in capabilities” around Cloud DBMS participation in broader data ecosystem and “a conscious aim to interoperate with them,” Gartner says. “If anything, progress toward this is faster than expected, with many significant vendor announcements since last year’s cloud DBMS Magic Quadrant.”

The trend toward playing in data ecosystems is a broader one that is not isolated to cloud DBMSs or DBMSs in general (you’ll remember back in 2019, when Gartner predicted that the cloud would usurp the majority of the DBMS market, which is the process of happening–55% of DBMS spending was on the cloud in 2022, Gartner says, and the cloud accounted for 98% of all growth in the entire DBMS market).

Gartner says that by 2025, 90% of new data and analytics deployments “will be through an established data ecosystem, causing consolidation across the data and analytics market.” What’s more, it says that by the end of next year, 55% of IT buyers will have adopted a data ecosystem. “That will consolidate the vendor landscape by 40%, thereby reducing cost while reducing choice,” the analyst group says.

Data Ecosystem Ratings

Gartner gave higher marks to some cloud DBMSs for their participation in data ecosystems. While it didn’t specifically mention data ecosystem participation or interoperability in all 19 of the vendor profiles in its Magic Quadrant, it did for 10 of them. Here’s a summary of what it said for those 10:

Recent partnerships Alibaba Cloud made with ISVs like MongoDB, ClickHouse and PingCAP has demonstrated improvement in its cloud ecosystem, Gartner says. “This provides more choice in third-party D&A [data and analytics] solutions with less integration effort on Alibaba Cloud,” Gartner says in its Magic Quadrant, which featured Alibaba Cloud in the Leaders quadrant.

(NicoElNino/Shutterstock)

Gartner also discussed AWS’s movements toward a data ecosystem. It states that the cloud giant has the resources “to move toward a more integrated set of solutions, building on the work started with Amazon DataZone,” the data management service that went GA last October and which is composed of a data portal, a data catalog, data projects and environments, and a governance and access control layer. However, Gartner also cautioned about going with an all-AWS eco-system, which raises lock-in concerns.

Cloudera, which Gartner put in its Visionaries quadrant, received Excellent Marks for its data ecosystem work. “Cloudera continues to invest in its open-source leadership to drive innovation through the community with open standards in its data ecosystem delivering portable data and AI services across all cloud data architectures,” Gartner says. “With a centralized control plane across all clouds and on-premises, it delivers integrated security, metadata and governance with applied observability and an open data ecosystem.”

Gartner noted that ecosystems available through cloud providers are more “tightly integrated” and are “easier to use” than Cloudera’s. However, Cloudera’s dedication to multi-cloud and hybrid deployments, and ease of portability on workloads, “is an effective counterbalance to this competitive pressure that will require sustained effort to remain effective,” Gartner says.

Couchbase, which develops a NoSQL database used primarily for transactional and operational use cases, was lauded by Gartner for its capabilities in mobile and edge and for the ease of use of Capella, its managed database service. However, Couchbase’s ecosystem support is lacking, according to Gartner, which placed Couchbase in the Niche Players quadrant.

“Couchbase does not have a full-fledged capability to access data nor provide data to engines outside of the Couchbase world, although they are on its roadmap,” the analyst group says. “The ability to broadly interact with multiple engines across an ecosystem is driving increasing flexibility and efficiency in multiple use cases, most prominently analytics and AI. Other nonrelational products also have this limitation.”

(phipatbig/Shutterstock)

Databricks, which Gartner placed in the Leaders quadrant, received Excellent Marks for Unity Catalog, the company’s metadata catalog and governance hub for data that exists in Databricks as well as outside repositories. Gartner also lauded the data ecosystem bonafides of Delta Live Tables for its capability to simplify ETL pipeline development for streaming, batch, and AI workloads.

Gartner also had good things to say about the data ecosystem participation of Google Cloud, which also launched in the Leader quadrant. In particular, Gartner applauded Dataplex, its metadata/governance layer that enables a more integrated data ecosystem.

Microsoft, which landed in Gartner’s Leaders quadrant, also got Excellent Marks for its willingness to make its database more open and to work with other Microsoft products, including Microsoft 365, Power BI, and Purview but also with external solutions from ISVs.

“This enables a more consistent experience for its clients,” Gartner says. “At the same time, the ‘one lake’ direction in Microsoft Fabric brings more openness to data in non-Microsoft systems, which the potential to reduce its clients’ vendor lock-in concerns.” However, some Microsoft customers have expressed concern about the complexity of Microsoft DBMSs ecosystem capabilities , which hurt performance, security, and cost control, Gartner says.

SAP, a Visionary in Gartner’s Magic Quadrant, was lauded for its capability to run operational and analytical workloads in the same HANA database. Gartner also liked SAP Datasphere’s capability to unify SAP and non-SAP data in an ecosystem play.

“SAP is now much more open in its ability to import and export data between SAP and non-SAP environments via file exchange, replication and federation,” Gartner says. However, few non-SAP customers are going to use SAP to manage data, the analyst group says. And Datasphere is likely to be used by customers with “a significant SAP technology presence.”

Snowflake, which develops an analytical data warehouse and is in the Leaders quadrant, also got a nod from Gartner for its “robust” ecosystem capabilities. “Snowflake promotes the philosophy of an easy-to-use integrated solution complemented by a robust data-sharing and data marketplace story,” Gartner says.

Teradata is another data warehouse provider playing in the data ecosystem. Gartner, which put Teradata in the Visionary quadrant, likes Teradata’s QueryGrid functionality, which “implements access to data outside of Teradata efficiently by intelligently pushing down processing where appropriate, offloading cycles from the Teradata machine, and reducing the amount of data that has to be returned to Teradata,” Gartner says.

Cloud DBMSs obviously have capabilities beyond their integration with third-party data management tools and broader data ecosystems. But as Gartner has shown, the ecosystem grade of a database is becoming a more important consideration for database buyers.

Databricks is offering a get for the full 2023 Gartner Magic Quadrant for CDBMS. You can access it here.

Related Items:

Cloud Databases Are Maturing Rapidly, Gartner Says

Who’s Winning the Cloud Database War

Cloud Now Default Platform for Databases, Gartner Says

Fri, 05 Jan 2024 02:44:00 -0600 text/html https://www.datanami.com/2024/01/05/how-broad-is-your-databases-data-ecosystem-gartner-takes-a-look/
Chapter 10: Information Theory and Source Coding No result found, try new keyword!Information theory provides a quantitative measure of the information contained in message signals and allows us to determine the capacity of a communication system to transfer this information from ... Sat, 17 Feb 2018 11:57:00 -0600 en-US text/html https://www.globalspec.com/reference/76532/203279/chapter-10-information-theory-and-source-coding How To Get An Open Source Developer Job In 2018
  • Demand for open source developers with container expertise is soaring, with 57% of hiring managers prioritizing this expertise in 2018, up from 27% last year.
  • Hiring managers are choosing to invest in and scale up new hires and existing employees by investing in training versus spending on external consultants.
  • Be active in the open source community and contribute the highest quality code and content possible.

The 2018 Open Source Jobs Report published by The Linux Foundation and Dice.com provides many useful insights into which skills are the most marketable, the technologies most affecting hiring decisions, and which incentives are most effective for retaining open source talent. Taken together the many insights in the study provide a useful roadmap for recently-graduated students and experienced open source, developers, and technical professionals. The study is based on a survey of over 750 hiring managers representing a cross-section of corporations, small & medium businesses (SMBs), government agencies and staffing firms worldwide in addition to 6,500 open source professionals. Additional details regarding the methodology can be found in the report downloadable here (PDF, 14 pp., opt-in).  The following findings show how strong demand is for developers with open source expertise and which skills are in the most demand.

  • The number of hiring managers seeking Linux talent soared in 2018 to 80% up from 65% in 2017, making this the most in-demand open source skill. Cloud technology experts are the second most in demand at 64%, followed by security and web technologies (49% each). Networking (46%) and containers (44%) are the six areas managers are prioritizing in their recruiting and hiring. Six in ten (62%) of open source professionals rank containers as the fastest growing area of 2018. 48% of open source developers believe Artificial intelligence and machine learning is growing the fastest followed by security (43%).
  • Knowledge of cloud, container and security technologies most affect who gets an offer according to hiring managers. Having deep expertise in Linux in addition to experience working with cloud, containers, security, and networking is an effective career strategy for getting an open source developer job and progressing in a technical career. 66% of hiring managers cited cloud computing as the technology that most affects their hiring decisions, followed by containers (57%), security (49%) and networking (47%).
  • Hiring managers are choosing to invest in and scale up new hires and existing employees by investing in training versus spending on external consultants.  55% of employers are now also offering to pay for employee certifications, up from 47% in 2017 and only 34% in 2016. Global Knowledge recently completed a study of which certifications are the most valuable, and they are summarized in the post, 15 Top Paying Certifications For 2018.  55% of employers are willing to pay for certifications today, up from 47% last year and 34% in 2016. 42% are using training as an incentive to retain employees, up from 33% last year and 26% in 2016.
  • Despite employers prioritizing pay to recruit open source developers, 65% are in the field to work with new technologies, 64% for the freedom of open source and 62% because they have a passion for the field. Open source developers who are the most likely to find a new job translate their passion for the field into shareable code and content. Getting a dream job as an open source developer starts by becoming part of the community and actively contributing as much as you can. Creating and sharing open source code via GitHub and other means, blogging and sharing what you’ve learned is a great way to stand out from other applicants. I recently had lunch with a good friend who is looking for an open source developer job and this person’s GitHub is getting a ton of downloads from a latest open source app written for data visualization. And a presentation given at a latest conference is leading to interview opportunities. The open source community is very reciprocal, and it’s a great idea to share the highest quality code and content there, and can lead to job interviews.
  • Open source skills are lucrative, and in high demand, with 87% of open source developers crediting their expertise and continual learning of new apps, languages, and tools as the reason they are advancing in their careers. 52% of hiring managers say they will hire more open source professionals in the next six months than they did in the previous six months, crediting their company’s growth as a result of a strong national & global economy. 60% of hiring managers say the number of available positions for open source developers in increasing at a faster pace than overall open positions. The market value of DevOps skills grew an average 7.1% during the past six months according to analyst firm Foote Partners.
  • There’s an 18% gap between what employees say is progress on diversity versus employers. Only 52% of open source developers say the level of effort at attaining greater diversity is effective versus 70% of employers. Employers need to consider how they can use advanced hiring systems beyond Applicant Tracking Systems (ATS) to get beyond the potential for conscious and unconscious bias in hiring decisions. A previous post, How to Close The Talent Gap With Machine Learning, provides insights into how employers can remove biases from hiring decisions and evaluate candidates on talent alone.
Tue, 14 Aug 2018 06:08:00 -0500 Louis Columbus en text/html https://www.forbes.com/sites/louiscolumbus/2018/08/14/how-to-get-an-open-source-developer-job-in-2018/
Anonymous Sources

Transparency is critical to our credibility with the public and our subscribers. Whenever possible, we pursue information on the record. When a newsmaker insists on background or off-the-record ground rules, we must adhere to a strict set of guidelines, enforced by AP news managers.

 Under AP's rules, material from anonymous sources may be used only if:

 1. The material is information and not opinion or speculation, and is vital to the report.

 2. The information is not available except under the conditions of anonymity imposed by the source.

 3. The source is reliable, and in a position to have direct knowledge of the information.

 Reporters who intend to use material from anonymous sources must get approval from their news manager before sending the story to the desk. The manager is responsible for vetting the material and making sure it meets AP guidelines. The manager must know the identity of the source, and is obligated, like the reporter, to keep the source's identity confidential. Only after they are assured that the source material has been vetted by a manager should editors and producers allow it to be used.

 Reporters should proceed with interviews on the assumption they are on the record. If the source wants to set conditions, these should be negotiated at the start of the interview. At the end of the interview, the reporter should try once again to move onto the record some or all of the information that was given on a background basis.

 The AP routinely seeks and requires more than one source when sourcing is anonymous. Stories should be held while attempts are made to reach additional sources for confirmation or elaboration. In rare cases, one source will be sufficient – when material comes from an authoritative figure who provides information so detailed that there is no question of its accuracy.

 We must explain in the story why the source requested anonymity. And, when it’s relevant, we must describe the source's motive for disclosing the information. If the story hinges on documents, as opposed to interviews, the reporter must describe how the documents were obtained, at least to the extent possible.

The story also must provide attribution that establishes the source's credibility; simply quoting "a source" is not allowed. We should be as descriptive as possible: "according to top White House aides" or "a senior official in the British Foreign Office." The description of a source must never be altered without consulting the reporter.

 We must not say that a person declined comment when that person the person is already quoted anonymously. And we should not attribute information to anonymous sources when it is obvious or well known. We should just state the information as fact.

Stories that use anonymous sources must carry a reporter's byline. If a reporter other than the bylined staffer contributes anonymous material to a story, that reporter should be given credit as a contributor to the story.

 All complaints and questions about the authenticity or veracity of anonymous material – from inside or outside the AP – must be promptly brought to the news manager's attention.

 Not everyone understands “off the record” or “on background” to mean the same things. Before any interview in which any degree of anonymity is expected, there should be a discussion in which the ground rules are set explicitly.

These are the AP’s definitions:

On the record. The information can be used with no caveats, quoting the source by name.

Off the record. The information cannot be used for publication. Background. The information can be published but only under conditions negotiated with the source. Generally, the sources do not want their names published but will agree to a description of their position. AP reporters should object vigorously when a source wants to brief a group of reporters on background and try to persuade the source to put the briefing on the record.

Deep background. The information can be used but without attribution. The source does not want to be identified in any way, even on condition of anonymity.

In general, information obtained under any of these circumstances can be pursued with other sources to be placed on the record.

ANONYMOUS SOURCES IN MATERIAL FROM OTHER NEWS SOURCES

Reports from other news organizations based on anonymous sources require the most careful scrutiny when we consider them for our report.

AP's basic rules for anonymous source material apply to material from other news outlets just as they do in our own reporting: The material must be factual and obtainable no other way. The story must be truly significant and newsworthy. Use of anonymous material must be authorized by a manager. The story we produce must be balanced, and comment must be sought.

Further, before picking up such a story we must make a bona fide effort to get it on the record, or, at a minimum, confirm it through our own reporting. We shouldn't hesitate to hold the story if we have any doubts. If another outlet’s anonymous material is ultimately used, it must be attributed to the originating news organization and note its description of the source.

ATTRIBUTION

 Anything in the AP news report that could reasonably be disputed should be attributed. We should give the full name of a source and as much information as needed to identify the source and explain why the person s credible. Where appropriate, include a source's age; title; name of company, organization or government department; and hometown. If we quote someone from a written document – a report, email or news release -- we should say so. Information taken from the internet must be vetted according to our standards of accuracy and attributed to the original source. File, library or archive photos, audio or videos must be identified as such. For lengthy stories, attribution can be contained in an extended editor's note detailing interviews, research and methodology.

Tue, 20 Jun 2023 05:32:00 -0500 en text/html https://www.ap.org/about/news-values-and-principles/telling-the-story/anonymous-sources
Cloudera Agrees to $5.3 Billion Takeover by KKR, Clayton Dubilier & Rice No result found, try new keyword!Carl Ichan-backed Cloudera agrees to a $5.3 billion takeover by private equity groups Kohlberg Kravis Roberts & Co and Clayton Dubilier & Rice. Kohlberg Kravis Roberts & Co and Clayton Dubilier ... Mon, 31 May 2021 22:40:00 -0500 text/html https://www.thestreet.com/investing/cloudera-agrees-5-3-billion-private-equity-takeover-lead-by-kkr The Importance of Information Sources at the Workplace

Lainie Petersen writes about business, real estate and personal finance, drawing on 25 years experience in publishing and education. Petersen's work appears in Money Crashers, Selling to the Masses, and in Walmart News Now, a blog for Walmart suppliers. She holds a master's degree in library science from Dominican University.

Wed, 18 Jul 2018 17:18:00 -0500 en-US text/html https://smallbusiness.chron.com/importance-information-sources-workplace-13809.html
ChatGPT found by study to spread inaccuracies when answering medication questions

ChatGPT has been found to have shared inaccurate information regarding drug usage, according to new research.

In a study led by Long Island University (LIU) in Brooklyn, New York, nearly 75% of drug-related, pharmacist-reviewed responses from the generative AI chatbot were found to be incomplete or wrong.

In some cases, ChatGPT, which was developed by OpenAI in San Francisco and released in late 2022, provided "inaccurate responses that could endanger patients," the American Society of Health System Pharmacists (ASHP), headquartered in Bethesda, Maryland, stated in a press release.

WHAT IS ARTIFICIAL INTELLIGENCE?

ChatGPT also generated "fake citations" when asked to cite references to support some responses, the same study also found.

Along with her team, lead study author Sara Grossman, PharmD, associate professor of pharmacy practice at LIU, asked the AI chatbot practice questions that were originally posed to LIU’s College of Pharmacy drug information service between 2022 and 2023.

ChatGPT, the AI chatbot created by OpenAI, generated inaccurate responses about medications, a new study has found. The company itself previously said that "OpenAI’s models are not fine-tuned to provide medical information. You should never use our models to provide diagnostic or treatment services for serious medical conditions,"  (LIONEL BONAVENTURE/AFP via Getty Images)

Of the 39 questions posed to ChatGPT, only 10 responses were deemed "satisfactory," according to the research team's criteria.

The study findings were presented at ASHP’s Midyear Clinical Meeting from Dec. 3 to Dec. 7 in Anaheim, California.

Grossman, the lead author, shared her initial reaction to the study's findings with Fox News Digital.

BREAST CANCER BREAKTHROUGH: AI PREDICTS A THIRD OF CASES PRIOR TO DIAGNOSIS IN MAMMOGRAPHY STUDY

Since "we had not used ChatGPT previously, we were surprised by ChatGPT’s ability to provide quite a bit of background information about the medication and/or disease state relevant to the question within a matter of seconds," she said via email. 

"Despite that, ChatGPT did not generate accurate and/or complete responses that directly addressed most questions."

Grossman also mentioned her surprise that ChatGPT was able to generate "fabricated references to support the information provided."

Out of 39 questions posed to ChatGPT, only 10 of the responses were deemed "satisfactory" according to the research team's criteria. (Frank Rumpenhorst/picture alliance via Getty Images; iStock)

In one example she cited from the study, ChatGPT was asked if "a drug interaction exists between Paxlovid, an antiviral medication used as a treatment for COVID-19, and verapamil, a medication used to lower blood pressure."

HEAD OF GOOGLE BARD BELIEVES AI CAN HELP Strengthen COMMUNICATION AND COMPASSION: ‘REALLY REMARKABLE’

The AI model responded that no interactions had been reported with this combination.

But in reality, Grossman said, the two drugs pose a potential threat of "excessive lowering of blood pressure" when combined.

"Without knowledge of this interaction, a patient may suffer from an unwanted and preventable side effect," she warned.

"It is always important to consult with health care professionals before using information that is generated by computers."

ChatGPT should not be considered an "authoritative source of medication-related information," Grossman emphasized.

"Anyone who uses ChatGPT should make sure to verify information obtained from trusted sources — namely pharmacists, physicians or other health care providers," Grossman added.

MILITARY MENTAL HEALTH IN FOCUS AS AI TRAINING SIMULATES REAL CONVERSATIONS TO HELP PREVENT VETERAN SUICIDE

The LIU study did not evaluate the responses of other generative AI platforms, Grossman pointed out — so there isn’t any data on how other AI models would perform under the same condition.

"Regardless, it is always important to consult with health care professionals before using information that is generated by computers, which are not familiar with a patient’s specific needs," she said.

Usage policy by ChatGPT

Fox News Digital reached out to OpenAI, the developer of ChatGPT, for comment on the new study.

OpenAI has a usage policy that disallows use for medical instruction, a company spokesperson previously told Fox News Digital in a statement.

Paxlovid, Pfizer's antiviral medication to treat COVID-19, is displayed in this picture illustration taken on Oct. 7, 2022. When ChatGPT was asked if a drug interaction exists between Paxlovid and verapamil, the chatbot answered incorrectly, a new study reported. (REUTERS/Wolfgang Rattay/Illustration)

"OpenAI’s models are not fine-tuned to provide medical information. You should never use our models to provide diagnostic or treatment services for serious medical conditions," the company spokesperson stated earlier this year. 

"OpenAI’s platforms should not be used to triage or manage life-threatening issues that need immediate attention."

Health care providers "must provide a disclaimer to users informing them that AI is being used and of its potential limitations." 

The company also requires that when using ChatGPT to interface with patients, health care providers "must provide a disclaimer to users informing them that AI is being used and of its potential limitations." 

In addition, as Fox News Digital previously noted, one big caveat is that ChatGPT’s source of data is the internet — and there is plenty of misinformation on the web, as most people are aware. 

That’s why the chatbot’s responses, however convincing they may sound, should always be vetted by a doctor.

The new study's author suggested consulting with a health care professional before relying on generative AI for medical inquiries. (iStock)

Additionally, ChatGPT was only "trained" on data up to September 2021, according to multiple sources. While it can increase its knowledge over time, it has limitations in terms of serving up more latest information.

Last month, CEO Sam Altman reportedly announced that OpenAI's ChatGPT had gotten an upgrade — and would soon be trained on data up to April 2023.

‘Innovative potential’

Dr. Harvey Castro, a Dallas, Texas-based board-certified emergency medicine physician and national speaker on AI in health care, weighed in on the "innovative potential" that ChatGPT offers in the medical arena.

"For general inquiries, ChatGPT can provide quick, accessible information, potentially reducing the workload on health care professionals," he told Fox News Digital.

ARTIFICIAL INTELLIGENCE HELPS DOCTORS PREDICT PATIENTS’ RISK OF DYING, STUDY FINDS: ‘SENSE OF URGENCY’

"ChatGPT's machine learning algorithms allow it to Strengthen over time, especially with proper reinforcement learning mechanisms," he also said.

ChatGPT’s recently reported response inaccuracies, however, pose a "critical issue" with the program, the AI expert pointed out.

"This is particularly concerning in high-stakes fields like medicine," Castro said.

A health tech expert noted that medical professionals are responsible for "guiding and critiquing" artificial intelligence models as they evolve.  (iStock)

Another potential risk is that ChatGPT has been shown to "hallucinate" information — meaning it might generate plausible but false or unverified content, Castro warned. 

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"This is dangerous in medical settings where accuracy is paramount," said Castro.

"While ChatGPT shows promise in health care, its current limitations … underscore the need for cautious implementation."

AI "currently lacks the deep, nuanced understanding of medical contexts" possessed by human health care professionals, Castro added.

"While ChatGPT shows promise in health care, its current limitations, particularly in handling drug-related queries, underscore the need for cautious implementation."

OpenAI, the developer of ChatGPT, has a usage policy that disallows use for medical instruction, a company spokesperson told Fox News Digital earlier this year. (Jaap Arriens/NurPhoto via Getty Images)

Speaking as an ER physician and AI health care consultant, Castro emphasized the "invaluable" role that medical professionals have in "guiding and critiquing this evolving technology."

CLICK HERE TO GET THE FOX NEWS APP

"Human oversight remains indispensable, ensuring that AI tools like ChatGPT are used as supplements rather than replacements for professional medical judgment," Castro added.

Melissa Rudy of Fox News Digital contributed reporting. 

For more Health articles, visit www.foxnews.com/health.

Wed, 13 Dec 2023 19:20:00 -0600 Fox News en text/html https://www.foxnews.com/health/chatgpt-found-study-spread-inaccuracies-when-answering-medication-questions
How To Become A Game Developer: Salary, Education Requirements And Job Growth

Editorial Note: We earn a commission from partner links on Forbes Advisor. Commissions do not affect our editors' opinions or evaluations.

If you’re a technology professional pursuing a career in the gaming industry, you might consider becoming a video game developer. These gaming experts create the framework for building video games across various platforms including mobile, computer and gaming devices.

The following sections offer a closer look at how to become a video game developer.

Video Game Developer Job Outlook

Since the first video game came onto the scene, the industry has seen exponential growth. As such, video game developers can expect fast career growth in the coming years.

The U.S. Bureau of Labor Statistics (BLS) does not provide data for video game developers specifically, but the BLS projects a faster-than-average 26% growth for software developers, quality assurance analysts and testers. Video game developers fall in with these professionals.

What Is a Video Game Developer?

Video game developers play a crucial role in the success of any video game. They are responsible for bringing a video game from concept to reality. To do this, video game developers must code and program visual elements and other features. They also run tests to make sure the game performs well.

Video Game Development vs. Video Game Design

You may hear the titles “video game developer” and “video game designer” used interchangeably, but the two jobs are different. Video game designers focus on the creative aspects of video game creation. Developers, on the other hand, focus on coding and the other technical aspects of that process.

What are the Main Responsibilities of a Video Game Developer?

Video game developer roles vary depending on the place of employment. In smaller organizations, for example, these professionals may work on multiple projects—such as both coding and testing—at the same time throughout the game development process.

At larger video game companies, on the other hand, each developer may take on a more specific set of tasks.

Typical responsibilities for a video game developer include:

  • Coding visual elements
  • Game design ideation
  • Making sure the game plays well
  • Monitoring game performance
  • Reviewing and improving existing code
  • Working with producers, designers and other professionals to bring the game to life

Video Game Developer Salary

Factors like experience and location affect video game developers’ salaries. Developers in the entertainment or video game software industry make an average annual salary of around $91,000, according to Payscale data as of December 2023.

Steps to Becoming a Video Game Developer

Several educational paths can lead to a video game developer career. Some developers attend college. Others opt for immersive bootcamps, where they learn crucial skills such as coding and technical problem-solving. Below, we take a look at the most important steps you need to take to land a job as a video game developer.

Earn a Degree

When it comes to the hiring process, many video game companies look for developers with degrees. A degree is not an absolute requirement, but employers may prefer candidates who have completed undergraduate degrees in computer science or related fields.

Given the gaming industry’s growing popularity, several colleges now offer bachelor’s degrees in video game design and development.

Obtain a Certificate

Certificates offer another option for students who want to either forgo college or supplement their current degree. Earning a certificate in video game development allows students to hone their skills through intensive, project-based curricula.

Entities like the University of Washington, Harvard University and Arkansas State University offer professional certificate programs in game development. Since these certificate programs generally take less than a year to complete, they can offer a quicker path to a career in the gaming industry than traditional four-year degrees.

Certificates cannot fully replace professional experience, but they do offer several benefits. For example, video game development certificate-holders can:

  • Build a solid foundation in game development and design.
  • Connect with groups of fellow creatives.
  • Meet teachers and mentors who can help make introductions to industry professionals.

Gain Work Experience

Professional experience is just as important as education when it comes to building a solid foundation in video game development. Before gaining professional experience or earning a degree, you might find entry-level work as a game tester. Game testing positions rarely require specialized training or a degree, so this might be a good way to build experience while completing your studies.

Many game developers begin their careers with internships as well. Consider pursuing an internship at a gaming studio to start making professional connections and building hands-on experience. You might also apply for non-development roles at gaming studios to get your foot in the door and start learning the ropes.

Video Game Development Bootcamps

Bootcamps can offer a strong alternative to traditional degrees for prospective video game developers. Bootcamps are short-term, intensive programs that offer specialized training for specific jobs. Though many employers prefer candidates with full degrees, bootcamps can also provide you with a high-quality education.

Examples of game development and design bootcamps include:

  • General Assembly. This online game design bootcamp focuses on the mechanics of gamification and how to engage users.
  • Vertex School. This 30-week, fully online program trains prospective developers to work in the gaming industry.
  • Udemy. This 11-hour crash course claims to teach “everything you need to become a game developer from scratch.”

Frequently Asked Questions (FAQs) About Video Game Development

How do I get into video game development?

Start with education. You can pursue a degree in computer science or game development, or you can complete a coding or game development bootcamp. You might then pursue an internship or entry-level role at a gaming studio.

How long does it take to become a game developer?

If you go the traditional route, it takes at least four years to complete a bachelor’s degree and gain some professional experience before you can become a game developer.

What does a video game developer do?

Game developers bring video games from concept to reality. This work involves lots of coding, programming, testing and maintenance.

Fri, 29 Jul 2022 04:12:00 -0500 Doug Shaffer en-US text/html https://www.forbes.com/advisor/education/how-to-become-a-video-game-developer/
The Savings Game: Better financial planning begins with good information sources No result found, try new keyword!In this column I'll share my recommendations for these sources. For information about IRAs and other retirement savings accounts, Ed Slott and his publications are simply the best. I regularly ... Wed, 06 Dec 2023 06:08:00 -0600 en-us text/html https://www.msn.com/




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