Spark Engine 2.4
| Component | 2.4-dataproc-16 | 2.4-dataproc-15 | 2.4-dataproc-14 | 2.4-dataproc-13 |
|---|---|---|---|---|
| Apache Spark | 2.4.8 | 2.4.8 | 2.4.8 | 2.4.8 |
| Hadoop Libraries | 2.10.2 | 2.10.2 | 2.10.2 | 2.10.2 |
| Cloud Storage Connector | hadoop2-2.1.9 | hadoop2-2.1.9 | hadoop2-2.1.9 | hadoop2-2.1.9 |
| Java | 8 | 8 | 8 | 8 |
| Python | 3.7.4 | 3.7.4 | 3.7.4 | 3.7.4 |
| Conda | 4.7.12 | 22.11.1 | 22.11.1 | 22.1.0 |
| R | 3.6.3 | 3.6.3 | 3.6.3 | 3.6.3 |
Spark Engine 3.1
| Component | 3.1-dataproc-16 | 3.1-dataproc-15 | 3.1-dataproc-14 | 3.1-dataproc-13 |
|---|---|---|---|---|
| Apache Spark | 3.1.3 | 3.1.3 | 3.1.3 | 3.1.3 |
| Hadoop Libraries | 3.2.3 | 3.2.3 | 3.2.3 | 3.2.3 |
| Cloud Storage Connector | hadoop3-2.2.13 | hadoop3-2.2.13 | hadoop3-2.2.11 | hadoop3-2.2.11 |
| Java | 8 | 8 | 8 | 8 |
| Python | 3.8.5 | 3.8.5 | 3.8.5 | 3.8.5 |
| Conda | 4.9.2 | 23.5.0 | 4.9.2 | 4.9.2 |
| R | 4.3.0 | 4.3.0 | 4.2.3 | 4.2.3 |
A fully qualified Spark engine release version is expressed as: 2.4-dataproc-[NUMBER] or
3.1-dataproc-[NUMBER], for example, 2.4-dataproc-3 or 3.1-dataproc-3.
Spark Version formats can also be expressed in alias form, as shown in the following examples:
2- Most recent version of Spark engine with a Spark major version of 22.4- Most recent version of Spark engine with a Spark major.minor version of 2.4.3- Most recent version of Spark engine with a Spark major version of 3.3.1- Most recent version of Spark engine with a Spark major.minor version of 3.1.dataproc-1.5- Most recent version of Spark engine that broadly aligns with Dataproc on Compute Engine1.5images.dataproc-2.0- Most recent version of Spark engine that broadly aligns with Dataproc on Compute Engine2.0images.latest- Most recent version of Spark engine.