How to Integrate MariaDB with Apache Spark in PostgreSQL

Galaxy Glossary

How do I connect Apache Spark to MariaDB for scalable analytics?

MariaDB–Spark integration lets Spark read from and write to MariaDB through the JDBC driver for large-scale analytics.

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Description

Example H2

Example H3

Why integrate MariaDB with Apache Spark?

Spark adds distributed processing to MariaDB’s transactional data. You can run heavy joins, aggregates, and ML pipelines without exporting CSVs or overloading the OLTP server.

What driver and dependencies are required?

Add the MariaDB JDBC JAR (e.g., org.mariadb.jdbc:mariadb-java-client:3.2.0). Spark shell example: spark-shell --packages org.mariadb.jdbc:mariadb-java-client:3.2.0.

How do I build the JDBC URL?

Format: jdbc:mariadb://HOST:PORT/DATABASE?user=USER&password=PW&ssl=true. Optional params: serverTimezone, socketTimeout, permitMysqlScheme.

How do I read a table into Spark?

Call spark.read.format("jdbc") with url, dbtable, user, and password. Add partitionColumn, lowerBound, upperBound, and numPartitions for parallel reads.

Example: Load Customers

val customers = spark.read.format("jdbc") .option("url", "jdbc:mariadb://db:3306/shop") .option("dbtable", "Customers") .option("user", "analytics") .option("password", sys.env("SHOP_PW")) .option("partitionColumn", "id") .option("lowerBound", "1") .option("upperBound", "500000") .option("numPartitions", "8") .load()

How do I combine MariaDB tables?

Create DataFrames for Orders, OrderItems, and Products, register temp views, then use Spark SQL.

Revenue per product per day

spark.sql(""" SELECT p.name, DATE(o.order_date) AS order_day, SUM(oi.quantity * p.price) AS revenue FROM orders o JOIN order_items oi ON o.id = oi.order_id JOIN products p ON p.id = oi.product_id GROUP BY p.name, order_day ORDER BY revenue DESC """).show()

How do I write results back?

Use df.write.mode("append").format("jdbc").options(jdbcOpts).save(). Provide createTableColumnTypes if Spark must create the table.

What permissions are required?

The MariaDB user needs SELECT on source tables and INSERT/UPDATE on targets. Restrict to analytics hosts for security.

Best practices for production

Enable SSL, cap fetch size (fetchsize=1000), and isolate analytics traffic on replicas. Monitor Spark executors to avoid long-running locks.

Common mistakes

Single-partition scans slow jobs. Always set partitioning options.

Missing driver JAR causes ClassNotFoundException. Confirm the JAR is on every Spark node.

Where can I learn more?

Check Apache Spark JDBC docs and MariaDB Connector/J guide for advanced parameters like allowPublicKeyRetrieval and failover hosts.

Why How to Integrate MariaDB with Apache Spark in PostgreSQL is important

How to Integrate MariaDB with Apache Spark in PostgreSQL Example Usage


-- Scala example: enrich Orders with customer emails and store to reporting schema
val orders  = spark.read.format("jdbc").options(jdbcOpts("Orders")).load()
val customers = spark.read.format("jdbc").options(jdbcOpts("Customers")).load()

val enriched = orders.join(customers, orders("customer_id") === customers("id"))
                     .select(orders("id").as("order_id"), customers("email"), orders("total_amount"))

enriched.write.mode("append").format("jdbc")
  .option("url", "jdbc:mariadb://db:3306/reporting")
  .option("dbtable", "OrderEmails")
  .option("user", "analytics")
  .option("password", sys.env("SHOP_PW"))
  .save()

How to Integrate MariaDB with Apache Spark in PostgreSQL Syntax


-- Spark read syntax
spark.read.format("jdbc")
  .option("url", "jdbc:mariadb://HOST:PORT/DB")
  .option("dbtable", "TABLE or (SELECT ...) AS alias")
  .option("user", "USER")
  .option("password", "PW")
  -- Optional parallelism
  .option("partitionColumn", "id")
  .option("lowerBound", "1")
  .option("upperBound", "1000000")
  .option("numPartitions", "16")
  -- Performance tweaks
  .option("fetchsize", "1000")
  .option("isolationLevel", "READ_COMMITTED")
  .load()

-- Spark write syntax
resultDF.write.mode("append")
  .format("jdbc")
  .option("url", "jdbc:mariadb://HOST:PORT/DB")
  .option("dbtable", "target_table")
  .option("user", "USER")
  .option("password", "PW")
  .option("batchsize", "5000")
  .save()

Common Mistakes

Omitting partitioning options reads all data through a single executor, causing hours-long scans. Fix by setting partitionColumn, lowerBound, upperBound, and numPartitions.
Forgetting to package the MariaDB JDBC driver leads to ClassNotFoundException at runtime. Always add the JAR with --packages or place it in $SPARK_HOME/jars.