☕ Java & Groovy for Data

Do the data half of the job in the language your company already runs — streams and records, JDBC and DuckDB, with Groovy for the parts where Java makes you type too much.

No lessons published yet — this is the roadmap, so you can see exactly what the course will cover before it lands.

Before you start: Learn SQL — Series 1. Series 1 of Learn SQL is the whole prerequisite: SELECT, WHERE, JOIN and GROUP BY. Once you start running queries from Java here, you check the answers against the same Northwind numbers the SQL koans use. You are never asked to write clever SQL — but you do need to read a query and know what it should come back with, because that is how you tell a JVM bug from a SQL one.

Short on time? The 31 episodes marked core are the shortest path to being productive at work. Start there and pick up the rest whenever a job asks for them.

Series 1 · Java & Groovy for Data Fundamentals

write a Java or Groovy script that reads and reshapes data

01
Your First Script — Read a CSV File and Answer One Question About It
corebeginner#foundationalcoming soon
02
Records and Collections — Holding Rows and Tables in Memory
corebeginnercoming soon
03
Streams — Transforming Rows With map, filter and collect
corebeginner#foundationalcoming soon
04
Groovy Collections — Filtering, Transforming and Grouping in Less Code
beginnercoming soon
05
Files and Encodings — Reading Text Files in the Right Character Set
corebeginnercoming soon
06
java.time — Working With Dates, Times and Time Zones Correctly
corebeginnercoming soon
07
Nulls and Optional — Handling Data That Is Missing
corebeginnercoming soon
08
Money and BigDecimal — Doing Arithmetic on Amounts and Rounding Them
corebeginnercoming soon
09
Grouping and Aggregating — Summarising Rows With groupingBy
corebeginnercoming soon
10
Joining Two Datasets in Memory — Combining Rows Without Doubling Totals
corebeginnercoming soon
11
Your First End-to-End Script — From a File to a Finished Answer
corebeginner#projectcoming soon

Series 2 · Working With Real Data

files, databases and APIs — nothing pre-cleaned

01
CSV, JSON and Parquet — Reading the Three Formats You Will Meet Most
coreintermediatecoming soon
02
Excel with POI — Reading and Writing the Spreadsheets Your Business Needs
intermediatecoming soon
03
PDF with PDFBox — Reading and Writing the Documents and Reports Your Business Needs
intermediatecoming soon
04
JDBC — Talking to a Database From Java: Connection, Statement, ResultSet
coreintermediate#foundationalcoming soon
05
PreparedStatement — Passing Values Safely Into a Query
coreintermediatecoming soon
06
Text Blocks — Writing Multi-Line SQL Inside Java Code
intermediatecoming soon
07
groovy.sql.Sql — Running Queries With Much Less Code
coreintermediatecoming soon
08
jOOQ — Writing SQL in Java That the Compiler Checks
intermediatecoming soon
09
MyBatis — Mapping Hand-Written SQL Onto Java Objects
intermediatecoming soon
10
Batches and Transactions — Inserting Many Rows Quickly and Safely
coreintermediatecoming soon
11
Streaming Large Results — Reading Millions of Rows Without Filling Memory
coreintermediatecoming soon
12
DuckDB from Java — An Analytics Engine Inside Your Process
intermediatecoming soon
13
Choosing Database Access — Picking Between JDBC, jOOQ, MyBatis and DuckDB
coreintermediatecoming soon
14
HTTP and JSON — Reading Data From an API With HttpClient and Jackson
coreintermediatecoming soon
15
Retry, Backoff and Pagination — Fetching From an API Reliably
intermediatecoming soon
16
Virtual Threads and Parallel Streams — Running Slow Calls in Parallel
intermediatecoming soon
17
Cleaning and Validating — Checking Data Before You Load It
coreintermediatecoming soon
18
Project — One Answer From a CSV, a Database and an API
coreintermediate#projectcoming soon

Series 3 · Java That Ships

code someone else can run next month

01
Maven, Gradle and @Grab — Dependencies for Apps and for Scripts
coreadvancedcoming soon
02
Project Structure — Where the Data Code Goes
advancedcoming soon
03
Command-Line Tools — Arguments, Exit Codes and picocli
coreadvancedcoming soon
04
Configuration and Secrets — Keeping Passwords Out of Your Code
coreadvancedcoming soon
05
Liquibase — Database Changes Kept in Version Control, Written in Groovy
coreadvancedcoming soon
06
Logging and Failure — What Someone Needs to See When the Job Breaks
coreadvancedcoming soon
07
Testing Data Code — Testcontainers and the Database You Actually Ship
advancedcoming soon
08
Performance and Memory — Measure Before You Change Anything
advancedcoming soon
09
Before You Reach for Threads — Push It Down to the Engine
coreadvancedcoming soon
10
Fan-Out and Bounded Memory — N Calls, One Queue, a Flat Heap
advancedcoming soon
11
Partitioned Work — Splitting Rows and Combining Answers
advanced#dean-mapreducecoming soon
12
When One Machine Is Not Enough — What Changes, and What Breaks
advancedcoming soon
13
Project — A Job That Reads, Transforms, Loads and Reports
coreadvanced#projectcoming soon

Series 4 · Frameworks, Where They Earn It

use JPA, Hibernate and Spring for queries and the jobs that run them

01
JPA — Java's Standard Way to Turn Rows Into Objects
advancedcoming soon
02
Hibernate — The Library That Turns Your JPA Code Into SQL
advancedcoming soon
03
Spring JdbcTemplate — Running Your Own SQL From a Spring Application
coreadvancedcoming soon
04
Spring Data Repositories — Your Method Name Becomes the Query
advancedcoming soon
05
GORM — Grails' Data Layer, and the Hibernate Underneath It
advancedcoming soon
06
Liquibase in Spring Boot and Grails — Migrations That Run at Startup
advancedcoming soon
07
Spring Batch — Jobs That Process Rows in Chunks and Restart Where They Stopped
advancedcoming soon
08
Apache Beam — Describing a Pipeline Once and Letting a Runner Execute It
advancedcoming soon
09
Spring Scheduling — Running a Data Job on a Timer Inside Your Application
advancedcoming soon
10
DataPallas Crons — Scheduling the dbt Transform and the Excel Refresh
coreadvancedcoming soon
11
ShedLock — Locking a Scheduled Task So Only One Instance Runs It
advancedcoming soon
12
Quartz — Storing Schedules in a Database and Firing Them Once Across Instances
advancedcoming soon
13
Choosing a Framework — Picking Between JPA, Spring Data, GORM, Spring Batch and Quartz
coreadvancedcoming soon
14
Project — Add a Data Feature to the DataPallas Grails App
coreadvanced#projectcoming soon

Where this leads

Grails — starts from Series 1, and Series 4.
Spring Boot — starts from Series 1, and Series 4.

Not here, on purpose

Controllers, dependency injection, security and the web layer — not covered; Series 4 teaches Spring and Grails only where they read and write rows
Hibernate internals and JPA entity mapping in depth — not covered by design. In this course, Series 4 · 00 teaches JPA as the vocabulary and Series 4 · 05 the one Hibernate behaviour that costs you memory on a bulk load
Deciding what the schema change should be — covered in Data Modeling, Series 2 · 50. In this course, Series 3 · 20 applies a change that has already been designed
Running a migration against a live database under load — locks, zero downtime — covered in Data Ops — here the question is only how the change gets versioned and shipped from your build
Making a load re-runnable — MERGE, watermarks and proving nothing changed — covered in ETL & Data Pipelines, Series 1 · 30 and · 35. In this course, Series 2 · 55 covers only the request-level half — whether it is safe to RETRY a call whose outcome you never learned
Machine learning — features, training, model selection — not covered; this track moves and shapes data. For LLM-era work see AI for Data
OCR, and getting data out of scanned documents — not covered. Series 2 · 07 teaches you to RECOGNISE that a PDF carries no text layer — which is the decision you actually have to make — but extracting from an image is a different tool and a different problem
Charts other people read, and dashboards — covered in BI & Data Visualization — here you plot only to see the data yourself
cron, systemd timers, and choosing an orchestrator — covered in Data Ops — here the scheduler runs inside your own Spring Boot app, which fails in different ways. In this course, Series 4 · 30 and · 35
Writing the SQL itself — covered in Learn SQL — here the SQL is assumed and the question is how to run it from the JVM

☕ Java & Groovy for Data

Series 1 · Java & Groovy for Data Fundamentals

Your First Script — Read a CSV File and Answer One Question About It

Records and Collections — Holding Rows and Tables in Memory

Streams — Transforming Rows With map, filter and collect

Groovy Collections — Filtering, Transforming and Grouping in Less Code

Files and Encodings — Reading Text Files in the Right Character Set

java.time — Working With Dates, Times and Time Zones Correctly

Nulls and Optional — Handling Data That Is Missing

Money and BigDecimal — Doing Arithmetic on Amounts and Rounding Them

Grouping and Aggregating — Summarising Rows With groupingBy

Joining Two Datasets in Memory — Combining Rows Without Doubling Totals

Your First End-to-End Script — From a File to a Finished Answer

Series 2 · Working With Real Data

CSV, JSON and Parquet — Reading the Three Formats You Will Meet Most

Excel with POI — Reading and Writing the Spreadsheets Your Business Needs

PDF with PDFBox — Reading and Writing the Documents and Reports Your Business Needs

JDBC — Talking to a Database From Java: Connection, Statement, ResultSet

PreparedStatement — Passing Values Safely Into a Query

Text Blocks — Writing Multi-Line SQL Inside Java Code

groovy.sql.Sql — Running Queries With Much Less Code

jOOQ — Writing SQL in Java That the Compiler Checks

MyBatis — Mapping Hand-Written SQL Onto Java Objects

Batches and Transactions — Inserting Many Rows Quickly and Safely

Streaming Large Results — Reading Millions of Rows Without Filling Memory

DuckDB from Java — An Analytics Engine Inside Your Process

Choosing Database Access — Picking Between JDBC, jOOQ, MyBatis and DuckDB

HTTP and JSON — Reading Data From an API With HttpClient and Jackson

Retry, Backoff and Pagination — Fetching From an API Reliably

Virtual Threads and Parallel Streams — Running Slow Calls in Parallel

Cleaning and Validating — Checking Data Before You Load It

Project — One Answer From a CSV, a Database and an API

Series 3 · Java That Ships

Maven, Gradle and @Grab — Dependencies for Apps and for Scripts

Project Structure — Where the Data Code Goes

Command-Line Tools — Arguments, Exit Codes and picocli

Configuration and Secrets — Keeping Passwords Out of Your Code

Liquibase — Database Changes Kept in Version Control, Written in Groovy

Logging and Failure — What Someone Needs to See When the Job Breaks

Testing Data Code — Testcontainers and the Database You Actually Ship

Performance and Memory — Measure Before You Change Anything

Before You Reach for Threads — Push It Down to the Engine

Fan-Out and Bounded Memory — N Calls, One Queue, a Flat Heap

Partitioned Work — Splitting Rows and Combining Answers

When One Machine Is Not Enough — What Changes, and What Breaks

Project — A Job That Reads, Transforms, Loads and Reports

Series 4 · Frameworks, Where They Earn It

JPA — Java's Standard Way to Turn Rows Into Objects

Hibernate — The Library That Turns Your JPA Code Into SQL

Spring JdbcTemplate — Running Your Own SQL From a Spring Application

Spring Data Repositories — Your Method Name Becomes the Query

GORM — Grails' Data Layer, and the Hibernate Underneath It

Liquibase in Spring Boot and Grails — Migrations That Run at Startup

Spring Batch — Jobs That Process Rows in Chunks and Restart Where They Stopped

Apache Beam — Describing a Pipeline Once and Letting a Runner Execute It

Spring Scheduling — Running a Data Job on a Timer Inside Your Application

DataPallas Crons — Scheduling the dbt Transform and the Excel Refresh

ShedLock — Locking a Scheduled Task So Only One Instance Runs It

Quartz — Storing Schedules in a Database and Firing Them Once Across Instances

Choosing a Framework — Picking Between JPA, Spring Data, GORM, Spring Batch and Quartz

Project — Add a Data Feature to the DataPallas Grails App

Where this leads

Not here, on purpose