This is an extension to Drools tutorial with Maven. This externalize the rules criteria to an Excel spreadsheet license.xls. This means the age condition is supplied in the xls file under src/main/resources/drools/license.xls. Step 1: Maven pom.xml file dependencies. … Read more ›...
This extends the 02: Getting started with Jenkins Multibranch pipeline on Docker tutorial. The focus on this tutorial is the build triggers where the Jenkins pipelines can be executed based on different triggers as opposed to just clicking on the “Build Now” … Read more ›...
The part 1 was a comprehensive beginner style Jasper Reports tutorial. This extends that to demonstrate how to pass parameters via a Map using name/value pairs to the Jasper Reports. Step 1: Add a new custom parameter named “footerText” … Read more ›...
This extends Java gRPC with flatbuffers & Maven tutorial step by step.
The only difference in this tutorial is to use flatc via a Docker image that has flatbuffers.
This tutorial uses the image neomantra/flatbuffers from Docker hub.
…
This tutorial extends JAXB Tutorial for XML processing in Java step by step – unmarshall & marshall When to use JAXB with StAX? When you want to process large XML files, reading the whole file into memory can cause “OutOfMemoryError” as discussed in Java String & … Read more ›...
Step 1: Add an additional method to save data.
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
package com.mytutorial.dao; import java.util.List; import com.mytutorial.model.Account; public interface AccountDao { public List<Account> getAccounts(); public boolean saveAccount(Account account); } |
Step 2: Implementation making use of a “PreparedStatement”.
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 |
package com.mytutorial.dao; import java.math.BigDecimal; import java.sql.Connection; import java.sql.PreparedStatement; import java.sql.ResultSet; import java.sql.SQLException; import java.sql.Statement; import java.util.ArrayList; import java.util.List; import com.mytutorial.model.Account; import com.mytutorial.util.ConnectionUtil; public class AccountDaoImpl implements AccountDao { public List<Account> getAccounts() { Connection conn = null; Statement stmnt = null; ResultSet rs = null; List<Account> accounts = new ArrayList<Account>(); try { conn = ConnectionUtil.getConnection(); stmnt = conn.createStatement(); rs = stmnt.executeQuery("SELECT * FROM Account"); while (rs.next()) { Account account = new Account(); account.setId(rs.getString("id")); account.setName(rs.getString("name")); float balance = rs.getFloat("balance"); account.setBalance(BigDecimal.valueOf(balance)); accounts.add(account); } } catch (SQLException sqle) { sqle.printStackTrace(); } finally { try { if (rs != null) { rs.close(); } if (stmnt != null) { stmnt.close(); } if (conn != null) { conn.close(); } } catch (Exception ex) { ex.printStackTrace(); } } return accounts; } @Override public boolean saveAccount(Account account) { Connection conn = null; PreparedStatement pStmnt = null; try { conn = ConnectionUtil.getConnection(); pStmnt = conn.prepareStatement("insert into account values (?,?,?)"); pStmnt.setString(1, account.getId()); pStmnt.setString(2, account.getName()); pStmnt.setFloat(3, account.getBalance().floatValue()); return pStmnt.execute(); } catch (SQLException sqle) { sqle.printStackTrace(); } finally { try { if (pStmnt != null) { pStmnt.close(); } if (conn != null) { conn.close(); } } catch (Exception ex) { ex.printStackTrace(); } } return false; } } |
Step 3: Finally, the JdbcExample.
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 |
package com.mytutorial.main; import java.math.BigDecimal; import java.util.List; import com.mytutorial.dao.AccountDao; import com.mytutorial.dao.AccountDaoImpl; import com.mytutorial.model.Account; public class JdbcExample { public static void main(String[] args) { AccountDao dao = new AccountDaoImpl(); List<Account> accounts = dao.getAccounts(); System.out.println(accounts); Account newAccount = new Account(); newAccount.setId("999"); newAccount.setName("Samuel JJ"); newAccount.setBalance(BigDecimal.valueOf(235.35)); dao.saveAccount(newAccount); accounts = dao.getAccounts(); System.out.println(accounts); } } |
…
Step 1: You need to have the Webspeher MQ client jar “com.ibm.mq.allclient.jar” in your project at “${basedir}/lib” and the JMS or JEE jar from a maven repository.
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 |
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> //..... <properties> <maven.compiler.source>1.7</maven.compiler.source> <maven.compiler.target>1.7</maven.compiler.target> <mq-client.version>8.0.0.0</mq-client.version> </properties> <repositories> <repository> <id>localrepository</id> <url>file://${basedir}/lib</url> </repository> </repositories> <dependencies> <!-- Websphere MQ Implementation --> <dependency> <groupId>com.ibm.mq</groupId> <artifactId>allclient</artifactId> <version>${mq-client.version}</version> </dependency> <!-- JMS API --> <dependency> <groupId>javax.jms</groupId> <artifactId>javax.jms-api</artifactId> <version>2.0.1</version> </dependency> //..... </dependencies> </project> |
Step 2: Use the “JMS API” to send a message to a queue using a file based JNDI.
…
This extends Kubernetes (i.e. Minikube) – deploy a node js service.
Docker containers & Kubernetes for deploying Spring Boot microservices. As mentioned earlier in Kubernetes, Docker & Microservices interview Questions & Answers.
Docker gives you application isolation, and solves the dependency hell issues.
…
These Hadoop tutorials assume that you have installed Cloudera QuickStart, which has the Hadoop eco system like HDFS, Spark, Hive, HBase, YARN, etc. AVRO (i.e row oriented) and Parquet (i.e. column oriented) file formats are HDFS (i.e. Hadoop Distributed File System) friendly binary data formats as they store data compressed...
Go has pointers. A pointer holds the memory address of a value.
Q01. What will be the output of the below Golang code?
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 |
package main import "fmt" type User struct { firstname string surname string age int } func (u User) Age() int { return u.age } func Age(u User) int { return u.age } func (u User) updateAge(age int){ u.age = age } func main() { user := User { firstname: "John", surname: "Davies", age: 35, } fmt.Println(Age(user)) user.updateAge(22) fmt.Println(user.Age()); } |
A01. The above code outputs:
|
1 2 3 |
35 35 |
Q02.
…
Q1 How will you go about reading a CSV file as shown below?
|
1 2 3 4 5 6 |
Portfolio,Account,PositionIndicator,Amount AA123,CURR-AUD,CREDIT,2244.14000000 AA123,CURR-AUD,CREDIT,5.60000000 AA123,CURR-AUD,DEBIT,2249.74000000 AA123,CURR-GBP,CREDIT,0.01000000 AA123,CURR-GBP,DEBIT,0.01000000 |
A1
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 |
#!/bin/bash # $# means number of arguments supplied to the command. In this case the file to to be read if [ $# != 1 ]; then echo "Usage: $0 input-file" exit 1 else infile=$1 fi # assign file descriptor 3 to input file exec 3< $infile # read till the end of the file until [ $done ] do read <&3 myline #$? is the exit code, and 0 means success and != 0 means not success. That is no line is read. if [ $? != 0 ]; then done=1 continue fi # process file data line-by-line in here echo $myline done |
Q2 How will you read and then write to another file?
|
1 2 3 4 5 6 |
Portfolio,Account,PositionIndicator,Amount AA123,CURR-AUD,CREDIT,2244.14000000 AA123,CURR-AUD,CREDIT,5.60000000 AA123,CURR-AUD,DEBIT,2249.74000000 AA123,CURR-GBP,CREDIT,0.01000000 AA123,CURR-GBP,DEBIT,0.01000000 |
A2
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
#!/bin/bash # $# means number of arguments supplied to the command if [ $# != 2 ]; then # $0 is the script name $1 is input file and $2 is output file echo "Usage: $0 input-file output-file" exit 1 else infile=$1 fi # assign file descriptor 3 to input file exec 3< $infile # read till the end of the file until [ $done ] do read <&3 myline #$? is the exit code, and 0 means success and != 0 means not success. That is no line is read. if [ $? != 0 ]; then done=1 continue fi # process file data line-by-line # append to output file. If you run it more than once, it keeps appending. echo $myline >> $2 done |
Q3 How will you read the file and then write to another file with CSV data in different order? …...
Pre-requisite: Docker is installed on your machine for Mac OS X (E.g. $ brew cask install docker) or Windows 10. Docker interview Q&As.
This tutorial extends Apache Zeppelin on Docker Tutorial – Docker pull from Docker hub and Spark stand-alone to read a file from local file system
|
1 2 3 4 5 6 7 |
val lines = sc.textFile("file:///zeppelin/seed/employees.txt") case class Employee (id: Integer, name: String, location: String, salary: Double ) val dfEmployees = lines.map(s => s.split(",")).map(s => Employee(s(0).toInt, s(1), s(2), s(3).toDouble)).toDF() |
1.…
This extends Spark submit – reading a file from HDFS. A SequenceFile is a flat file consisting of binary key/value pairs. It is extensively used in MapReduce as input/output formats. Like CSV, Sequence files do not store meta data, hence only schema evolution is appending new fields to the end...