How to Integrate PostgreSQL with Apache Spark

Galaxy Glossary

How do I integrate PostgreSQL with Apache Spark for scalable analytics?

Use Spark’s JDBC connector to read, process, and write PostgreSQL data at scale.

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Description

Example H2

Example H3

What does integrating PostgreSQL with Apache Spark allow?

Integration lets you pull large PostgreSQL tables into Spark DataFrames, run distributed transformations, and push aggregated results back—without ETL pipelines.

Why choose Spark over pure SQL for heavy analytics?

Spark distributes computation across a cluster, so joins, window functions, and ML workloads finish in minutes instead of hours on a single Postgres server.

How do I read PostgreSQL tables into a Spark DataFrame?

Use spark.read.format("jdbc") with the JDBC URL, driver, dbtable, user, and password options. Partition columns and predicates speed parallel reads.

// Scala or PySpark val df = spark.read .format("jdbc") .option("url", "jdbc:postgresql://db:5432/shop") .option("dbtable", "public.Orders") .option("user", "analytics") .option("password", sys.env("PG_PW")) .option("partitionColumn", "id") .option("lowerBound", 1) .option("upperBound", 100000) .option("numPartitions", 8) .load()

How do I join DataFrames from multiple Postgres tables?

Read Customers, Orders, and OrderItems separately, then use DataFrame joins. Broadcast small tables like Products to reduce shuffle.

val joined = orders.join(customers, "customer_id") .join(products, "product_id")

How do I write Spark results back to PostgreSQL?

Call DataFrame.write.format("jdbc") with mode("overwrite" | "append"). Batch size and isolation level control throughput and safety.

agg.write .format("jdbc") .option("url", "jdbc:postgresql://db:5432/shop") .option("dbtable", "public.daily_sales") .option("user", "analytics") .option("password", sys.env("PG_PW")) .option("batchsize", 10000) .mode("append") .save()

What performance settings matter most?

Match numPartitions to cluster cores, push down predicates with filter clauses, and configure fetchsize (e.g., 10 000) to reduce round-trips.

How can I secure credentials?

Store secrets in environment variables or tools like HashiCorp Vault. Avoid hard-coding passwords in notebooks or git repos.

What are common mistakes and fixes?

Using a non-indexed partition column stalls reads—index id or date columns. Forgetting to set jdbcTimezone can shift timestamps; always align to UTC.

Why How to Integrate PostgreSQL with Apache Spark is important

How to Integrate PostgreSQL with Apache Spark Example Usage


-- Load Orders, join with Customers, aggregate, and save daily revenue
val orders = spark.read.format("jdbc")
  .option("url", "jdbc:postgresql://db:5432/shop")
  .option("dbtable", "public.Orders")
  .option("user", "analytics")
  .option("password", sys.env("PG_PW"))
  .load()

val customers = spark.read.format("jdbc")
  .option("url", "jdbc:postgresql://db:5432/shop")
  .option("dbtable", "public.Customers")
  .option("user", "analytics")
  .option("password", sys.env("PG_PW"))
  .load()

val revenue = orders.join(customers, orders("customer_id") === customers("id"))
  .groupBy("order_date")
  .agg(sum("total_amount").alias("daily_total"))

revenue.write.format("jdbc")
  .option("url", "jdbc:postgresql://db:5432/shop")
  .option("dbtable", "public.daily_revenue")
  .option("user", "analytics")
  .option("password", sys.env("PG_PW"))
  .mode("append")
  .save()

How to Integrate PostgreSQL with Apache Spark Syntax


spark.read.format("jdbc")
  .option("url", "jdbc:postgresql://<host>:<port>/<database>")
  .option("driver", "org.postgresql.Driver")
  .option("dbtable", "<schema>.<table> | (SELECT ...) t")
  .option("user", "<username>")
  .option("password", "<password>")
  [ .option("partitionColumn", "<numeric_col>")
    .option("lowerBound", <min>)
    .option("upperBound", <max>)
    .option("numPartitions", <n>) ]
  [ .option("fetchsize", <rows>) ]
  [ .option("jdbcTimezone", "UTC") ]
  .load()

spark.write.format("jdbc")
  .option("url", "jdbc:postgresql://<host>:<port>/<database>")
  .option("dbtable", "<schema>.<table>")
  .option("user", "<username>")
  .option("password", "<password>")
  [ .option("batchsize", <rows>) ]
  .mode("append" | "overwrite")
  .save()

Common Mistakes

Using an unindexed partitionColumn. Without an index, Spark creates many parallel JDBC scans that each trigger sequential scans in PostgreSQL, crippling the database. Always pick an indexed numeric or date column or add the needed index.
Ignoring jdbcTimezone. Postgres stores timestamps in UTC, but Spark defaults to the cluster timezone. Without jdbcTimezone="UTC", date shifts appear in your results. Set jdbcTimezone to UTC (or your desired zone) during reads and writes.