2026-04-10 23:20:41 -04:00
---
layout: default
title: "Yapı ı ı ı ı ı ı
parent: "Turkish (Beta)"
---
2026-04-11 01:08:44 +00:00
# Yapı ı ı ı ı ı ı
2026-04-10 23:20:41 -04:00
> **Beta Translation:** This document was translated via Machine Learning and as such may not be 100% accurate. All non-English languages are currently classified as Beta.
2026-04-11 01:08:44 +00:00
## Genel Bakı
Yapı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı ı
## Temel Kavramlar
### 1. Format Tanı ı
Giriş dosya türünü ve ayrı ı ı ı ı ı ı ı ı ı ı ı ı ı
### 2. Alan Eşlemeleri
Kaynak yolları ı ı ı ı ı ı ı ı ı
### 3. Dönüşüm Süreci
Alan değerlerine uygulanabilecek veri dönüşüm zinciri. Şunları
Veri temizleme (boşlukları ı
Biçim dönüştürme (tarih ayrı ı
Hesaplamalar (aritmetik işlemler, dize manipülasyonu)
Arama tabloları ı
### 4. Doğrulama Kuralları
Veri bütünlüğünü sağlamak için uygulanan veri kalitesi kontrolleri:
Tür doğrulama
Aralı
Desen eşleştirme (regex)
Gerekli alan doğrulama
Özel doğrulama mantı ı
### 5. Genel Ayarlar
Tüm içe aktarma sürecine uygulanan yapı ı
Veri zenginleştirme için arama tabloları
Küresel değişkenler ve sabitler
Çı ı
Hata işleme politikaları
## Uygulama Stratejisi
İçe aktarı ı ı ı
1. **Yapı ı ı ı ı - JSON tanı ı ı ı ı ı
2. **Ayrı ı ı ı ı - `format.type` 'a göre uygun ayrı ı ı ı ı
3. **Ön İşleme Uygula** - Küresel filtreleri ve dönüşümleri çalı ı ı
4. **Kayı ı - Her giriş kaydı
Kaynak yolları ı ı ı ı
Alan düzeyindeki dönüşümleri sı ı
Sonuçları ı ı ı
Eksik veriler için varsayı ı
5. **Son İşleme Uygula** - Tekilleştirme, birleştirme, vb. işlemlerini gerçekleştirin
6. **Çı ı ı - Verileri belirtilen hedef biçimde oluşturun
## Yol İfadesi Desteği
Farklı ı ı
**CSV**: Sütun adları `"column_name"` veya `"[2]"` )
**JSON**: JSONPath sözdizimi (`"$.user.profile.email"` )
**XML**: XPath ifadeleri (`"//product[@id='123']/price"` )
**Sabit genişlik**: Alan tanı ı ı
## Avantajlar
**Tek Kod Tabanı ı ı ı ı
**Kullanı ı ı ı ı ı
**Yeniden Kullanı ı ı ı
**Esnek** - Özel kodlama olmadan karmaşı
**Sağlam** - Yerleşik doğrulama ve kapsamlı
**Bakı ı ı ı ı ı ı ı
## Dil Özellikleri
Yapı ı ı ı ı ı ı ı ı ı ı ı
```json
{
"version": "1.0",
"metadata": {
"name": "Configuration Name",
"description": "Description of what this config does",
"author": "Author Name",
"created": "2024-01-01T00:00:00Z"
},
"format": { ... },
"globals": { ... },
"preprocessing": [ ... ],
"mappings": [ ... ],
"postprocessing": [ ... ],
"output": { ... }
}
```
### Biçim Tanı ı
Giriş verisi biçimini ve ayrı ı ı
```json
{
"format": {
"type": "csv|json|xml|fixed-width|excel|parquet",
"encoding": "utf-8",
"options": {
// Format-specific options
}
}
}
```
#### CSV Format Seçenekleri
```json
{
"format": {
"type": "csv",
"options": {
"delimiter": ",",
"quote_char": "\"",
"escape_char": "\\",
"skip_rows": 1,
"has_header": true,
"null_values": ["", "NULL", "null", "N/A"]
}
}
}
```
#### JSON Formatı
```json
{
"format": {
"type": "json",
"options": {
"root_path": "$.data",
"array_mode": "records|single",
"flatten": false
}
}
}
```
#### XML Formatı
```json
{
"format": {
"type": "xml",
"options": {
"root_element": "//records/record",
"namespaces": {
"ns": "http://example.com/namespace"
}
}
}
}
```
### Küresel Ayarlar
Arama tabloları ı ı ı ı ı ı
```json
{
"globals": {
"variables": {
"current_date": "2024-01-01",
"batch_id": "BATCH_001",
"default_confidence": 0.8
},
"lookup_tables": {
"country_codes": {
"US": "United States",
"UK": "United Kingdom",
"CA": "Canada"
},
"status_mapping": {
"1": "active",
"0": "inactive"
}
},
"constants": {
"source_system": "legacy_crm",
"import_type": "full"
}
}
}
```
### Alan Eşlemeleri
Dönüşümlerle birlikte kaynak verilerinin hedef alanlara nası ı ı
```json
{
"mappings": [
{
"target_field": "person_name",
"source": "$.name",
"transforms": [
{"type": "trim"},
{"type": "title_case"},
{"type": "required"}
],
"validation": [
{"type": "min_length", "value": 2},
{"type": "max_length", "value": 100},
{"type": "pattern", "value": "^[A-Za-z\\s]+$"}
]
},
{
"target_field": "age",
"source": "$.age",
"transforms": [
{"type": "to_int"},
{"type": "default", "value": 0}
],
"validation": [
{"type": "range", "min": 0, "max": 150}
]
},
{
"target_field": "country",
"source": "$.country_code",
"transforms": [
{"type": "lookup", "table": "country_codes"},
{"type": "default", "value": "Unknown"}
]
}
]
}
```
### Dönüşüm Türleri
Kullanı ı
#### String Dönüşümleri
```json
{"type": "trim"},
{"type": "upper"},
{"type": "lower"},
{"type": "title_case"},
{"type": "replace", "pattern": "old", "replacement": "new"},
{"type": "regex_replace", "pattern": "\\d+", "replacement": "XXX"},
{"type": "substring", "start": 0, "end": 10},
{"type": "pad_left", "length": 10, "char": "0"}
```
#### Tür Dönüşümleri
```json
{"type": "to_string"},
{"type": "to_int"},
{"type": "to_float"},
{"type": "to_bool"},
{"type": "to_date", "format": "YYYY-MM-DD"},
{"type": "parse_json"}
```
#### Veri İşlemleri
```json
{"type": "default", "value": "default_value"},
{"type": "lookup", "table": "table_name"},
{"type": "concat", "values": ["field1", " - ", "field2"]},
{"type": "calculate", "expression": "${field1} + ${field2}"},
{"type": "conditional", "condition": "${age} > 18", "true_value": "adult", "false_value": "minor"}
```
### Doğrulama Kuralları
Yapı ı ı
#### Temel Doğrulamalar
```json
{"type": "required"},
{"type": "not_null"},
{"type": "min_length", "value": 5},
{"type": "max_length", "value": 100},
{"type": "range", "min": 0, "max": 1000},
{"type": "pattern", "value": "^[A-Z]{2,3}$"},
{"type": "in_list", "values": ["active", "inactive", "pending"]}
```
#### Özel Doğrulamalar
```json
{
"type": "custom",
"expression": "${age} >= 18 & & ${country} == 'US'",
"message": "Must be 18+ and in US"
},
{
"type": "cross_field",
"fields": ["start_date", "end_date"],
"expression": "${start_date} < ${end_date}",
"message": "Start date must be before end date"
}
```
### Ön İşleme ve Son İşleme
Alan eşlemesi öncesinde/sonrası
```json
{
"preprocessing": [
{
"type": "filter",
"condition": "${status} != 'deleted'"
},
{
"type": "sort",
"field": "created_date",
"order": "asc"
}
],
"postprocessing": [
{
"type": "deduplicate",
"key_fields": ["email", "phone"]
},
{
"type": "aggregate",
"group_by": ["country"],
"functions": {
"total_count": {"type": "count"},
"avg_age": {"type": "avg", "field": "age"}
}
}
]
}
```
### Çı ı ı ı ı
İşlenmiş verilerin nası ı ı ı ı
```json
{
"output": {
"format": "trustgraph-objects",
"schema_name": "person",
"options": {
"batch_size": 1000,
"confidence": 0.9,
"source_span_field": "raw_text",
"metadata": {
"source": "crm_import",
"version": "1.0"
}
},
"error_handling": {
"on_validation_error": "skip|fail|log",
"on_transform_error": "skip|fail|default",
"max_errors": 100,
"error_output": "errors.json"
}
}
}
```
## Tam Bir Örnek
```json
{
"version": "1.0",
"metadata": {
"name": "Customer Import from CRM CSV",
"description": "Imports customer data from legacy CRM system",
"author": "Data Team",
"created": "2024-01-01T00:00:00Z"
},
"format": {
"type": "csv",
"encoding": "utf-8",
"options": {
"delimiter": ",",
"has_header": true,
"skip_rows": 1
}
},
"globals": {
"variables": {
"import_date": "2024-01-01",
"default_confidence": 0.85
},
"lookup_tables": {
"country_codes": {
"US": "United States",
"CA": "Canada",
"UK": "United Kingdom"
}
}
},
"preprocessing": [
{
"type": "filter",
"condition": "${status} == 'active'"
}
],
"mappings": [
{
"target_field": "full_name",
"source": "customer_name",
"transforms": [
{"type": "trim"},
{"type": "title_case"}
],
"validation": [
{"type": "required"},
{"type": "min_length", "value": 2}
]
},
{
"target_field": "email",
"source": "email_address",
"transforms": [
{"type": "trim"},
{"type": "lower"}
],
"validation": [
{"type": "pattern", "value": "^[\\w.-]+@[\\w.-]+\\.[a-zA-Z]{2,}$"}
]
},
{
"target_field": "age",
"source": "age",
"transforms": [
{"type": "to_int"},
{"type": "default", "value": 0}
],
"validation": [
{"type": "range", "min": 0, "max": 120}
]
},
{
"target_field": "country",
"source": "country_code",
"transforms": [
{"type": "lookup", "table": "country_codes"},
{"type": "default", "value": "Unknown"}
]
}
],
"output": {
"format": "trustgraph-objects",
"schema_name": "customer",
"options": {
"confidence": "${default_confidence}",
"batch_size": 500
},
"error_handling": {
"on_validation_error": "log",
"max_errors": 50
}
}
}
```
## Açı ı ı
Aşağı ı ı ı ı ı ı ı
```
I need you to analyze the provided data sample and create a Structured Data Descriptor configuration in JSON format.
The descriptor should follow this specification:
- version: "1.0"
- metadata: Configuration name, description, author, and creation date
- format: Input format type and parsing options
- globals: Variables, lookup tables, and constants
- preprocessing: Filters and transformations applied before mapping
- mappings: Field-by-field mapping from source to target with transformations and validations
- postprocessing: Operations like deduplication or aggregation
- output: Target format and error handling configuration
ANALYZE THE DATA:
1. Identify the format (CSV, JSON, XML, etc.)
2. Detect delimiters, encodings, and structure
3. Find data types for each field
4. Identify patterns and constraints
5. Look for fields that need cleaning or transformation
6. Find relationships between fields
7. Identify lookup opportunities (codes that map to values)
8. Detect required vs optional fields
CREATE THE DESCRIPTOR:
For each field in the sample data:
- Map it to an appropriate target field name
- Add necessary transformations (trim, case conversion, type casting)
- Include appropriate validations (required, patterns, ranges)
- Set defaults for missing values
Include preprocessing if needed:
- Filters to exclude invalid records
- Sorting requirements
Include postprocessing if beneficial:
- Deduplication on key fields
- Aggregation for summary data
Configure output for TrustGraph:
- format: "trustgraph-objects"
- schema_name: Based on the data entity type
- Appropriate error handling
DATA SAMPLE:
[Insert data sample here]
ADDITIONAL CONTEXT (optional):
- Target schema name: [if known]
- Business rules: [any specific requirements]
- Data quality issues to address: [known problems]
Generate a complete, valid Structured Data Descriptor configuration that will properly import this data into TrustGraph. Include comments explaining key decisions.
```
### Örnek Kullanı
```
I need you to analyze the provided data sample and create a Structured Data Descriptor configuration in JSON format.
[Standard instructions from above...]
DATA SAMPLE:
```csv
MüşteriID,Ad,E-posta,Yaş,Ülke,Durum,Kayı ı ı
1001,"Smith, John",john.smith@email .com,35,US,1,2023-01-15,5420.50
1002,"doe, jane",JANE.DOE@GMAIL .COM,28,CA,1,2023-03-22,3200.00
1003,"Bob Johnson",bob@,62,UK,0,2022-11-01,0
1004,"Alice Chen","alice.chen@company .org",41,US,1,2023-06-10,8900.25
1005,,invalid-email,25,XX,1,2024-01-01,100
```
ADDITIONAL CONTEXT:
- Target schema name: customer
- Business rules: Email should be valid and lowercase, names should be title case
- Data quality issues: Some emails are invalid, some names are missing, country codes need mapping
```
### Mevcut Verileri Örnek Olmadan Analiz Etme İsteği
```
I need you to help me create a Structured Data Descriptor configuration for importing [data type] data.
The source data has these characteristics:
- Format: [CSV/JSON/XML/etc]
- Fields: [list the fields]
- Data quality issues: [describe any known issues]
- Volume: [approximate number of records]
Requirements:
- [List any specific transformation needs]
- [List any validation requirements]
- [List any business rules]
Please generate a Structured Data Descriptor configuration that will:
1. Parse the input format correctly
2. Clean and standardize the data
3. Validate according to the requirements
4. Handle errors gracefully
5. Output in TrustGraph ExtractedObject format
Focus on making the configuration robust and reusable.
2026-04-10 23:20:41 -04:00
```
