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[English](./README.md) | [Chinese](./README-zh.md)
# TsFile Tools Manual
## Introduction

## Development

### Prerequisites

To build the Java version of TsFile Tools, you must have the following dependencies installed:

1. Java >= 17. Make sure the environment variable is set.
2. Maven >= 3.6 (if you are compiling TsFile from source).

### Build with Maven

```sh
mvn clean package -P with-java -DskipTests
```

### Install to local machine

```
mvn install -P with-java -DskipTests
```

## Schema Definition

### Parameters

| Parameter | Description | Required | Default |
|-----------|------------|----------|---------|
| table_name | Table name | Yes | |
| time_precision | Time precision (ms / us / ns / s) | No | ms |
| has_header | Whether CSV contains a header (true / false). Ignored for Parquet / Arrow. | No | true |
| separator | CSV delimiter (, / tab / ;). Ignored for Parquet / Arrow. | No | , |
| null_format | String value treated as null in CSV. Ignored for Parquet / Arrow (native null). | No | |
| tag_columns | Tag columns (device identifiers / primary key). Supports virtual columns with DEFAULT value. | No | |
| time_column | Time column name | Yes | |
| source_columns | Column definitions mapping to source file columns | Yes | |

> **Backward compatibility**: `id_columns` and `csv_columns` are still accepted as aliases for `tag_columns` and `source_columns`.

### Column Concepts

- **time_column**: Exactly one per table. Written as `time` column with type `TIMESTAMP` in TsFile.
- **tag_columns**: Device identifiers (composite primary key), 0 or more. Supports virtual columns not present in the source file via `DEFAULT` keyword.
  - **Data type is always `STRING`** and cannot be changed. Any type declared for a tag column in `source_columns` is ignored. We recommend writing tag columns in `source_columns` with the column name only (no type).
- **source_columns**: Maps every column in the source file by position (CSV) or by name (Parquet / Arrow). Use `SKIP` to ignore a column.
- **FIELD** (derived, not configured): All columns in `source_columns` that are not `time_column`, not in `tag_columns`, and not `SKIP`. These are the measurement columns whose values change over time.

> **Column name case**: TsFile table-model column and table names are case-insensitive and stored as lowercase. Regardless of whether you write `Time` / `TIME` / `time` in `import.schema`, the on-disk and read-back name is `time`.

### Schema Example

> Duplicate timestamps within the same device are not supported — rows sharing identical tag column values and the same timestamp will fail to write.

CSV file content:
```
Region,FactoryNumber,DeviceNumber,Model,MaintenanceCycle,Time,Temperature,Emission
hebei,1001,1,10,1,1,80.0,1000.0
hebei,1001,1,10,1,4,80.0,1000.0
hebei,1002,7,5,2,1,90.0,1200.0
```

Schema file (`import.schema`):
```
table_name=root.db1
time_precision=ms
has_header=true
separator=,
null_format=\N

tag_columns
Group DEFAULT Datang
Region
FactoryNumber
DeviceNumber

time_column=Time

source_columns
Region,
FactoryNumber,
DeviceNumber,
SKIP,
SKIP,
Time INT64,
Temperature FLOAT,
Emission DOUBLE,
```

In this example:
- `Group` is a virtual tag column (not in CSV) with default value `Datang`
- `Region`, `FactoryNumber`, `DeviceNumber` are tag columns read from CSV; their type is fixed as `STRING` and need not be declared
- `Model` and `MaintenanceCycle` are skipped via `SKIP`
- `Temperature` and `Emission` are automatically derived as FIELD columns

For Parquet / Arrow in schema mode, `source_columns` matches by column **name** instead of position. Named SKIP is also supported:
```
source_columns
Time INT64,
unused_col SKIP,
Temperature FLOAT,
Emission DOUBLE,
```

**Validation rules for Parquet / Arrow schema mode** (enforced — mismatches raise an error and the source file is moved to `--fail_dir`):

- **Column count must match exactly.** The number of entries in `source_columns` must equal the number of columns in the Parquet / Arrow file. Use `SKIP` for any file column you don't want to import.
- **Every name must exist in the source file.** Each non-SKIP column name and every named SKIP must resolve to an actual column in the file.
- **Unnamed `SKIP` is not allowed.** Because matching is by name, an unqualified `SKIP` cannot identify a column. Always use `columnName SKIP`.

## CLI Parameters

| Parameter | Description | Required | Default |
|-----------|------------|----------|---------|
| -s, --source | Input file or directory | Yes | |
| -t, --target | Output directory | Yes | |
| --schema | Schema file path. Omit for auto mode. | No | |
| --fail_dir | Directory for failed source files | No | failed |
| --format | Source format: csv / parquet / arrow. Auto-detected by file extension if omitted. | No | auto-detect |
| --table_name | Table name override (auto mode) | No | derived from filename |
| --time_precision | Time precision override (auto mode): ms / us / ns / s | No | ms |
| --separator | CSV delimiter (auto mode): , / tab / ; | No | , |
| -b, --block_size | CSV chunk size (e.g. 256M, 1G) | No | 256M |
| -tn, --thread_num | Thread count for parallel processing | No | 8 |

## Modes

### Schema Mode

Provide a `--schema` file to explicitly define column mapping, types, tags, and time column.

```sh
# CSV
csv2tsfile.sh --source ./data/csv --target ./output --fail_dir ./failed --schema ./schema/import.schema
csv2tsfile.bat --source .\data\csv --target .\output --fail_dir .\failed --schema .\schema\import.schema

# Parquet
parquet2tsfile.sh --source ./data/parquet --target ./output --fail_dir ./failed --schema ./schema/import.schema
parquet2tsfile.bat --source .\data\parquet --target .\output --fail_dir .\failed --schema .\schema\import.schema

# Arrow
arrow2tsfile.sh --source ./data/arrow --target ./output --fail_dir ./failed --schema ./schema/import.schema
arrow2tsfile.bat --source .\data\arrow --target .\output --fail_dir .\failed --schema .\schema\import.schema
```

### Auto Mode

Omit `--schema` to automatically infer column types and detect the time column.

**Auto mode rules:**
- **Time column**: must be named exactly `time` or `TIME` (case-sensitive, strict match).
  - Parquet / Arrow: if the source file contains multiple Timestamp-typed columns, only the one named `time` / `TIME` is selected as the time axis. The remaining Timestamp columns become FIELD columns and are stored as `INT64` (raw value preserved, TIMESTAMP semantic dropped). To keep them as `TIMESTAMP`, switch to schema mode and declare them explicitly.
- All other columns become FIELD (no tag inference)
- **CSV type inference** uses a 100-row sampling window per column. Each non-null cell is classified into a base type (BOOLEAN / INT64 / DOUBLE / STRING).
  - If only one base type appears across the sampled rows for a column, that type is used.
  - When **different base types appear in the same column**, the column is promoted: INT64 + DOUBLE → DOUBLE; any other mixed combination (including BOOLEAN with any numeric type) → STRING.
- Parquet / Arrow use native schema types directly
- **Default table name**: derived from the source filename (e.g. `sensor.csv` → table `sensor`). Sanitization rules applied in order:
  1. Strip the file extension (`.csv` / `.parquet` / `.arrow` / `.ipc` / `.feather`, or the last `.`-suffix as a fallback).
  2. Keep only ASCII letters (`a–z`, `A–Z`), digits (`0–9`), underscore (`_`), and dot (`.`). Every other character is replaced with `_`.
  3. Collapse consecutive `_` into a single `_`; strip leading and trailing `_`.
  4. If the result is empty, use a format-specific default: `csv_data` / `parquet_data` / `arrow_data`.
  5. If the result starts with a digit, prefix `t_` (TsFile table names cannot start with a digit).
- Default null tokens (CSV only): empty cell and `\N`

**Auto mode example:**

CSV file (`sensor.csv`):
```
time,temperature,humidity,status
1000,25.5,60.0,true
2000,26.1,55.3,false
3000,27.0,58.1,true
```

Auto mode infers:
```
table name:  sensor        (from filename)
time column: time
fields:      temperature DOUBLE, humidity DOUBLE, status BOOLEAN
tags:        (none)
```

**Commands:**
```sh
# CSV
csv2tsfile.sh --source ./data/csv --target ./output --fail_dir ./failed
csv2tsfile.bat --source .\data\csv --target .\output --fail_dir .\failed

# CSV with options
csv2tsfile.sh --source ./data/csv --target ./output --table_name my_table --separator tab --time_precision us

# Parquet
parquet2tsfile.sh --source ./data/parquet --target ./output --fail_dir ./failed
parquet2tsfile.bat --source .\data\parquet --target .\output --fail_dir .\failed

# Arrow (.arrow / .ipc / .feather)
arrow2tsfile.sh --source ./data/arrow --target ./output --fail_dir ./failed
arrow2tsfile.bat --source .\data\arrow --target .\output --fail_dir .\failed
```

### Output File Naming

- Single batch: `{source_basename}.tsfile`
- Multiple batches: `{source_basename}_1.tsfile`, `{source_basename}_2.tsfile`, ...
- Table name and output filename are independent — table name comes from schema or `--table_name`, filename comes from source file.