---
license: mit
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: live_cpu_utilization (TsFile)
configs:
- config_name: default
  data_files:
  - split: train
    path: live_cpu_utilization_g0.tsfile
  - split: train
    path: live_cpu_utilization_g1.tsfile
---

# live_cpu_utilization (TsFile)

Apache TsFile version of [`ICOS-AI/live_cpu_utilization`](https://huggingface.co/datasets/ICOS-AI/live_cpu_utilization).

## Overview

- **Tables:** 2 TsFile table(s), 2,488 rows in total.
  - `live_cpu_utilization_g0`: 499 rows, 2023-06-28 16:26:24 鈫?2023-06-29 01:05:58 (UTC)
  - `live_cpu_utilization_g1`: 1,989 rows, 2024-09-02 13:55:00 鈫?2024-09-09 11:35:00 (UTC)

## Schema (TsFile structure)

### `live_cpu_utilization_g0.tsfile`

- **Time** (INT64, milliseconds) 鈥?the source `Date` column.
- **TAG**: none 鈥?the table is stored as a single device.
- **FIELD** (10): `CPU_Core_0_Usage` (string), `CPU_Core_1_Usage` (double), `CPU_Core_2_Usage` (double), `CPU_Core_3_Usage` (double), `CPU_Core_4_Usage` (double), `CPU_Core_5_Usage` (double), `CPU_Core_6_Usage` (double), `CPU_Core_7_Usage` (double), `CPU_Usage_All_Cores` (double), `Memory_Usage` (double)

### `live_cpu_utilization_g1.tsfile`

- **Time** (INT64, milliseconds) 鈥?the source `timestamp` column.
- **TAG**: none 鈥?the table is stored as a single device.
- **FIELD** (2): `CPU` (double), `MEM` (double)

## Conversion notes

- One TsFile per source table (2 tables). Tables whose source carries several entities per file are stored as one device per entity.
- Time = the table's own clock column as INT64 milliseconds. The clock columns used here are `Date`, `timestamp`.
- No column is dropped. Rows that share a timestamp inside one device are ordered by a 1 ms step in stable source order, so calendar columns keep their exact day.

## Usage

> **Read this dataset with the Java SDK.** It is written with the `zstd` compressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (`pip install tsfile`) implements only `UNCOMPRESSED`, `SNAPPY`, `GZIP` and `LZ4`; opening this file with it yields no rows.

Read a converted file with the Apache TsFile Java SDK (`org.apache.tsfile:tsfile`):

```java
import org.apache.tsfile.file.metadata.IDeviceID;
import org.apache.tsfile.read.TsFileReader;
import org.apache.tsfile.read.TsFileSequenceReader;
import org.apache.tsfile.read.common.Path;
import org.apache.tsfile.read.expression.QueryExpression;
import org.apache.tsfile.read.query.dataset.QueryDataSet;
import org.apache.tsfile.write.schema.MeasurementSchema;

import java.util.ArrayList;
import java.util.List;

String path = "live_cpu_utilization_g0.tsfile";
try (TsFileSequenceReader sequenceReader = new TsFileSequenceReader(path);
     TsFileReader reader = new TsFileReader(sequenceReader)) {
    // Devices are enumerated as IDeviceID objects. Tables with TAG columns
    // have multi-segment device ids that cannot be rebuilt from their string
    // form, so always use getAllDevices() rather than getAllDeviceIds().
    for (IDeviceID device : sequenceReader.getAllDevices()) {
        List<Path> paths = new ArrayList<>();
        for (MeasurementSchema schema : reader.getMeasurement(device)) {
            String name = schema.getMeasurementName();
            if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) {
                paths.add(new Path(device, name, true));
            }
        }
        QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null));
        while (dataSet.hasNext()) {
            System.out.println(dataSet.next());
        }
    }
}
```

## Source & license

- Original dataset: [`ICOS-AI/live_cpu_utilization`](https://huggingface.co/datasets/ICOS-AI/live_cpu_utilization)
- License: mit (as declared by the original dataset).