mcpField
T
transform-maps

transform-maps

github.com/serac-labs数据与数据库7759 次安装9 周前更新
代码仓库

关于 transform-maps

面向 ServiceNow 数据导入配置的技能,涵盖导入集、转换映射和字段处理。适用于需要将外部数据导入 ServiceNow 表并控制更新或插入逻辑的场景。

主要功能

  1. 01配置多种数据源
  2. 02创建导入集暂存表
  3. 03映射并转换字段
  4. 04通过合并键更新记录
  5. 05使用脚本处理导入生命周期

适用场景

  1. 01将 CSV 或数据库数据导入 ServiceNow
  2. 02把源字段映射到目标表字段
  3. 03按员工编号更新现有记录

MCP 相关

README 提及 MCP 工具,可创建转换映射、字段映射和导入集,也可发现数据源并测试集成。

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/serac-labs/serac --skill transform-maps

安装后在 Claude Code 中输入/transform-maps确认已加载。

详细介绍

ServiceNow 转换映射

转换映射用于控制如何将导入集中的数据映射并转换到 ServiceNow 表中。

导入架构

Data Source (CSV, LDAP, JDBC, REST)
        ↓
    Import Set Table (staging)
        ↓
    Transform Map (mapping rules)
        ↓
    Target Table (final destination)

主要组件

组件表用途
数据源sys_data_source连接配置
导入集表sys_db_object暂存表
导入集sys_import_set导入运行记录
转换映射sys_transform_map映射定义
字段映射sys_transform_entry字段映射

数据源

CSV 数据源(ES5)
// Create CSV data source
var ds = new GlideRecord("sys_data_source")
ds.initialize()
ds.setValue("name", "Employee Import - CSV")
ds.setValue("type", "File")
ds.setValue("format", "CSV")

// File settings
ds.setValue("file_path", "/import/employees.csv")
ds.setValue("header_row", 1)

// CSV parsing
ds.setValue("csv_delimiter", ",")
ds.setValue("csv_quote", '"')

// Import set table
ds.setValue("import_set_table", "u_employee_import")

ds.insert()
JDBC 数据源(ES5)
// Create JDBC data source
var ds = new GlideRecord("sys_data_source")
ds.initialize()
ds.setValue("name", "HR System - JDBC")
ds.setValue("type", "JDBC")

// Connection
ds.setValue("connection_url", "jdbc:oracle:thin:@hrdb:1521:HRPROD")
ds.setValue("username", "hr_readonly")
ds.setValue("password", "encrypted_password")

// Query
ds.setValue("query", "SELECT emp_id, first_name, last_name, email, dept_code FROM employees WHERE active = 1")

// Import set table
ds.setValue("import_set_table", "u_hr_employee_import")

ds.insert()
REST 数据源(ES5)
// Create REST data source
var ds = new GlideRecord("sys_data_source")
ds.initialize()
ds.setValue("name", "External API - REST")
ds.setValue("type", "REST (IntegrationHub)")

// REST message
ds.setValue("rest_message", restMessageSysId)
ds.setValue("http_method", "GET")

// Response handling
ds.setValue("json_path", "$.data.employees[*]")

// Import set table
ds.setValue("import_set_table", "u_api_employee_import")

ds.insert()

导入集表

创建导入集表(ES5)
// Create staging table for employee import
var table = new GlideRecord("sys_db_object")
table.initialize()
table.setValue("name", "u_employee_import")
table.setValue("label", "Employee Import")
table.setValue("super_class", "sys_import_set_row") // Extends import set row
table.setValue("is_extendable", false)
table.insert()

// Add columns matching source data
var columns = [
  { name: "u_employee_id", type: "string", max_length: 50 },
  { name: "u_first_name", type: "string", max_length: 100 },
  { name: "u_last_name", type: "string", max_length: 100 },
  { name: "u_email", type: "string", max_length: 255 },
  { name: "u_department", type: "string", max_length: 100 },
  { name: "u_manager_id", type: "string", max_length: 50 },
  { name: "u_start_date", type: "string", max_length: 20 },
]

for (var i = 0; i < columns.length; i++) {
  var col = new GlideRecord("sys_dictionary")
  col.initialize()
  col.setValue("name", "u_employee_import")
  col.setValue("element", columns[i].name)
  col.setValue("internal_type", columns[i].type)
  col.setValue("max_length", columns[i].max_length)
  col.insert()
}

转换映射

创建转换映射(ES5)
// Create transform map
var tm = new GlideRecord("sys_transform_map")
tm.initialize()
tm.setValue("name", "Employee Import Transform")
tm.setValue("source_table", "u_employee_import")
tm.setValue("target_table", "sys_user")

// Run order (for multiple transforms)
tm.setValue("order", 100)

// Active
tm.setValue("active", true)

// Copy empty fields
tm.setValue("copy_empty_fields", false)

// Enforce mandatory fields
tm.setValue("enforce_mandatory_fields", true)

var tmSysId = tm.insert()

字段映射

直接字段映射(ES5)
// Map source fields to target fields
function addFieldMap(transformMapId, sourceField, targetField, config) {
  var fm = new GlideRecord("sys_transform_entry")
  fm.initialize()
  fm.setValue("map", transformMapId)
  fm.setValue("source_field", sourceField)
  fm.setValue("target_field", targetField)

  // Coalesce (match existing records)
  if (config && config.coalesce) {
    fm.setValue("coalesce", true)
  }

  // Order
  fm.setValue("order", config ? config.order : 100)

  return fm.insert()
}

// Map employee fields
addFieldMap(tmSysId, "u_employee_id", "employee_number", { coalesce: true, order: 10 })
addFieldMap(tmSysId, "u_first_name", "first_name", { order: 20 })
addFieldMap(tmSysId, "u_last_name", "last_name", { order: 30 })
addFieldMap(tmSysId, "u_email", "email", { order: 40 })
引用字段映射(ES5)
// Map to reference field (lookup by value)
var deptMap = new GlideRecord("sys_transform_entry")
deptMap.initialize()
deptMap.setValue("map", tmSysId)
deptMap.setValue("source_field", "u_department")
deptMap.setValue("target_field", "department")

// Reference handling
deptMap.setValue("reference_key", true)
deptMap.setValue("reference_key_field", "name") // Lookup by department name

// Create if not found
deptMap.setValue("create_also", false)

deptMap.insert()
脚本字段映射(ES5)
// Script-based field transformation
var scriptMap = new GlideRecord("sys_transform_entry")
scriptMap.initialize()
scriptMap.setValue("map", tmSysId)
scriptMap.setValue("target_field", "name")
scriptMap.setValue(
  "source_script",
  "// Combine first and last name\n" + 'answer = source.u_first_name + " " + source.u_last_name;',
)
scriptMap.insert()

// Date transformation script
var dateMap = new GlideRecord("sys_transform_entry")
dateMap.initialize()
dateMap.setValue("map", tmSysId)
dateMap.setValue("target_field", "u_start_date")
dateMap.setValue(
  "source_script",
  "// Convert MM/DD/YYYY to ServiceNow date format\n" +
    'var parts = source.u_start_date.split("/");\n' +
    "if (parts.length === 3) {\n" +
    '    answer = parts[2] + "-" + parts[0] + "-" + parts[1];\n' +
    "} else {\n" +
    '    answer = "";\n' +
    "}",
)
dateMap.insert()

合并(更新与插入)

合并配置
// Coalesce on employee_number to update existing records
var coalesceMap = new GlideRecord("sys_transform_entry")
coalesceMap.initialize()
coalesceMap.setValue("map", tmSysId)
coalesceMap.setValue("source_field", "u_employee_id")
coalesceMap.setValue("target_field", "employee_number")
coalesceMap.setValue("coalesce", true) // KEY: Use for matching
coalesceMap.setValue("order", 1) // Process first
coalesceMap.insert()

// Multiple coalesce fields (compound key)
// First field with coalesce=true, second with coalesce=true
// Both must match for update

转换脚本

onBefore 脚本(ES5)
// Transform Map > onBefore script
// Runs before each row is processed

;(function runTransformScript(source, map, log, target) {
  // Skip inactive employees
  if (source.u_status === "INACTIVE") {
    ignore = true // Skip this row
    return
  }

  // Validate required fields
  if (!source.u_employee_id || !source.u_email) {
    log.error("Missing required fields for row: " + source.sys_id)
    ignore = true
    return
  }

  // Normalize email
  source.u_email = source.u_email.toString().toLowerCase()
})(source, map, log, target)
onAfter 脚本(ES5)
// Transform Map > onAfter script
// Runs after each row is processed

;(function runTransformScript(source, map, log, target) {
  // Add user to appropriate group based on department
  if (target && action !== "ignore") {
    var dept = target.department.getDisplayValue()
    var groupName = ""

    if (dept === "IT") {
      groupName = "IT Staff"
    } else if (dept === "HR") {
      groupName = "HR Team"
    }

    if (groupName) {
      addUserToGroup(target.sys_id, groupName)
    }
  }

  function addUserToGroup(userId, groupName) {
    var group = new GlideRecord("sys_user_group")
    group.addQuery("name", groupName)
    group.query()

    if (group.next()) {
      var member = new GlideRecord("sys_user_grmember")
      member.addQuery("user", userId)
      member.addQuery("group", group.getUniqueValue())
      member.query()

      if (!member.next()) {
        member.initialize()
        member.setValue("user", userId)
        member.setValue("group", group.getUniqueValue())
        member.insert()
      }
    }
  }
})(source, map, log, target)
onComplete 脚本(ES5)
// Transform Map > onComplete script
// Runs after all rows are processed

;(function runTransformScript(source, map, log, target) {
  // Log import statistics
  var importSet = new GlideRecord("sys_import_set")
  if (importSet.get(source.sys_import_set)) {
    var stats = {
      total: importSet.getValue("rows"),
      inserted: importSet.getValue("insertions"),
      updated: importSet.getValue("updates"),
      errors: importSet.getValue("errors"),
    }

    log.info("Import completed: " + JSON.stringify(stats))

    // Send notification if errors
    if (stats.errors > 0) {
      gs.eventQueue("import.errors", importSet, stats.errors.toString())
    }
  }
})(source, map, log, target)

运行导入

手动执行导入(ES5)
// Execute import programmatically
var loader = new GlideImportSetLoader(dataSourceSysId)
var importSetSysId = loader.loadImportSet()

if (importSetSysId) {
  // Run transform
  var transformer = new GlideImportSetTransformer()
  transformer.setImportSetID(importSetSysId)
  transformer.transform()

  // Check results
  var importSet = new GlideRecord("sys_import_set")
  if (importSet.get(importSetSysId)) {
    gs.info("Import completed: " + importSet.getValue("state"))
    gs.info("Rows: " + importSet.getValue("rows"))
    gs.info("Errors: " + importSet.getValue("errors"))
  }
}

MCP 工具集成

可用的导入工具
工具用途
snow_create_transform_map创建转换映射
snow_create_field_map添加字段映射
snow_create_import_set创建导入集
snow_discover_data_sources查找数据源
snow_test_integration测试连接
示例工作流
// 1. Create import set table, then add one column per field
await snow_create_table({
  name: "u_vendor_import",
  label: "Vendor Import",
  extends_table: "sys_import_set_row",
})

await snow_create_field({ table: "u_vendor_import", column_name: "u_vendor_id", internal_type: "string" })
await snow_create_field({ table: "u_vendor_import", column_name: "u_vendor_name", internal_type: "string" })
await snow_create_field({ table: "u_vendor_import", column_name: "u_contact_email", internal_type: "string" })

// 2. Create transform map
var transformId = await snow_create_transform_map({
  name: "Vendor Import",
  source_table: "u_vendor_import",
  target_table: "core_company",
})

// 3. Add field mappings
await snow_create_field_map({
  transform_map: transformId,
  source: "u_vendor_id",
  target: "vendor_code",
  coalesce: true,
})

await snow_create_field_map({
  transform_map: transformId,
  source: "u_vendor_name",
  target: "name",
})

// 4. Stage rows into the import set table, then run the transform
var importResult = await snow_create_import_set({
  table: "u_vendor_import",
  data: [
    { u_vendor_id: "V001", u_vendor_name: "Acme Corp", u_contact_email: "[email protected]" },
  ],
})

await snow_execute_transform({
  import_set_sys_id: importResult.import_set,
  transform_map_sys_id: transformId,
})

最佳实践

  1. 暂存表 - 始终使用导入集表
  2. 合并键 - 定义明确的匹配条件
  3. 验证数据 - 使用 onBefore 脚本
  4. 错误处理 - 记录并处理失败
  5. 增量导入 - 跟踪上次导入日期
  6. 测试 - 先使用小型数据集进行测试
  7. 回滚计划 - 确保能够撤销导入
  8. 计划调度 - 使用计划数据源

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