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- Spark Development Guide
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- Practical Tutorial
- API Documentation
- FAQs
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- Contact Us
- Release Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- EMR on CVM Operation Guide
- Planning Cluster
- Configuring Cluster
- Managing Cluster
- Instance Information
- Node Specification Management
- Checking and Updating Public IP
- Logging in to Clusters
- Cluster Scale-Out
- Cluster Scale-in
- Releasing Now
- Auto Scaling
- Graceful Scale-In
- Changing Configurations
- Automatic Replacement
- Exporting Software Configuration
- Cluster Scripts
- Cluster Termination
- Operation Logs
- Task Center
- Disk Management
- Managing Service
- Monitoring and Alarms
- Cluster Overview
- Node Status
- Service Status
- Cluster Event
- Log
- Application Analysis
- Cluster Inspection
- Java Analysis
- Monitoring Metrics
- Node Monitoring Metrics
- HDFS Monitoring Metrics
- YARN Monitoring Metrics
- ZooKeeper Monitoring Metrics
- HBase Monitoring Metrics
- Hive Monitoring Metrics
- Spark Monitoring Metrics
- Presto Monitoring Metrics
- Trino Monitoring Metrics
- ClickHouse Monitoring Metrics
- Druid Monitoring Metrics
- Kudu Monitoring Metrics
- Alluxio Monitoring Metrics
- PrestoSQL Monitoring Metrics
- Impala Monitoring Metrics
- Ranger Monitoring Metrics
- COSRanger Monitoring Metrics
- Doris Monitoring Metrics
- Kylin Monitoring Metrics
- Zeppelin Monitoring Metrics
- Oozie Monitoring Metrics
- Storm Monitoring Metrics
- Livy Monitoring Metrics
- Kyuubi Monitoring Metrics
- StarRocks Monitoring Metrics
- Kafka Monitoring Metrics
- Alarm Configurations
- Alarm Records
- EMR on TKE Operation Guide
- EMR Serverless HBase Operation Guide
- EMR Development Guide
- Hadoop Development Guide
- HDFS Common Operations
- HDFS Federation Management Development Guide
- HDFS Federation Management
- Submitting MapReduce Tasks
- Automatically Adding Task Nodes Without Assigning ApplicationMasters
- YARN Task Queue Management
- Practices on YARN Label Scheduling
- Hadoop Practical Tutorial
- Using API to Analyze Data in HDFS and COS
- Dumping YARN Job Logs to COS
- Spark Development Guide
- Hbase Development Guide
- Phoenix on Hbase Development Guide
- Hive Development Guide
- Presto Development Guide
- Sqoop Development Guide
- Hue Development Guide
- Oozie Development Guide
- Flume Development Guide
- Kerberos Development Guide
- Knox Development Guide
- Alluxio Development Guide
- Kylin Development Guide
- Livy Development Guide
- Kyuubi Development Guide
- Zeppelin Development Guide
- Hudi Development Guide
- Superset Development Guide
- Impala Development Guide
- Druid Development Guide
- TensorFlow Development Guide
- Kudu Development Guide
- Ranger Development Guide
- Kafka Development Guide
- Iceberg Development Guide
- StarRocks Development Guide
- Flink Development Guide
- Hadoop Development Guide
- Practical Tutorial
- API Documentation
- FAQs
- Service Level Agreement
- Contact Us
Overview
This feature allows you to perform an overall analysis of HDFS storage, including the total number of files, total storage usage, file distribution, and recent trends in file storage as of the day before the current day (T-1). It also provides top directory lists for large and small files.
You can view the daily changes and recent trends in the total number of files and total storage usage based on HDFS storage within a cluster.
The file count and storage usage pie charts can help you understand the proportion of small files and the storage used by them.
The feature also allows you to query and download directory information for the top 1,000 large/small files as of the last collection time.
Directions
1. Log in to the EMR console and click the ID/Name of the corresponding cluster in the cluster list.
2. On the cluster details page, click Cluster Service and choose Operation > File Storage Analysis in the top-right corner of the HDFS component block to view information about relevant files stored on HDFS and their directories as of the last collection time.
3. Obtain statistical views.
3.1 You can view the daily increase and day-over-day change in the total number of files stored on HDFS and total storage usage.
3.2 Pie charts are provided to show you the numbers of empty files (size = 0 MB), small files (size ≤ 2 MB), other files (2 MB < size < 128 MB), and large files (size ≥ 128 MB), and the storage used by each of the four categories of files.
4. You can view recent trends in the number and storage usage of different categories of files.
5. You can query and download information about the top 1,000 small/large files as of the day before the current day (T-1), including the file name, file path, file size, user group, owner, and last access time.
Risk description
The data required for file storage analysis is collected at 14:00 (Beijing time) every day.
1. The file storage analysis involves collecting and analyzing backup FsImage files, which can increase the memory usage of the local machine (a maximum increase of 4 GB). If the proportion of machines in the cluster that are using memory consistently remains at a high level, you can submit a ticket to disable the feature.
2.. In HA clusters, the analysis feature is executed on the Standby Master node, while in non-HA clusters, the feature is executed on the Master node.
Yes
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