Demo: DiskBlockManager and Block Data¶

The demo shows how Spark stores data blocks on local disk (using DiskBlockManager and DiskStore among the services).

Configure Local Directories¶

Spark uses spark.local.dir configuration property for one or more local directories to store data blocks.

Start spark-shell with the property set to a directory of your choice (say local-dirs). Use one directory for easier monitoring.

$SPARK_HOME/bin/spark-shell --conf spark.local.dir=local-dirs

When started, Spark will create a proper directory layout. You are interested in blockmgr-[uuid] directory.

"Create" Data Blocks¶

Execute the following Spark application that forces persisting (caching) data to disk.

import org.apache.spark.storage.StorageLevel
spark.range(2).persist(StorageLevel.DISK_ONLY).count

Observe Block Files¶

Go to the blockmgr-[uuid] directory and observe the block files. There should be a few. Do you know how many and why?

$ tree local-dirs/blockmgr-b7167b5a-ae8d-404b-8de2-1a0fb101fe00/
local-dirs/blockmgr-b7167b5a-ae8d-404b-8de2-1a0fb101fe00/
├── 00
├── 04
│   └── shuffle_0_8_0.data
├── 06
├── 08
│   └── shuffle_0_8_0.index
...
├── 37
│   └── shuffle_0_7_0.index
├── 38
│   └── shuffle_0_4_0.data
├── 39
│   └── shuffle_0_9_0.index
└── 3a
    └── shuffle_0_6_0.data

47 directories, 48 files

Use web UI¶

Open http://localhost:4040 and switch to Storage tab (at http://localhost:4040/storage/). You should see one RDD cached.

Storage tab in web UI

Click the link in RDD Name column and review the information.

Enable Logging¶

Enable ALL logging level for org.apache.spark.storage.DiskStore and org.apache.spark.storage.DiskBlockManager loggers to have an even deeper insight on the block storage internals.

log4j.logger.org.apache.spark.storage.DiskBlockManager=ALL
log4j.logger.org.apache.spark.storage.DiskStore=ALL