Shinichi-Nakagawa

# リソースグループ
resource "azurerm_resource_group" "example" {
  name     = "example-rg"
  location = "East US"
}

# Container App の作成（システム割り当てマネージド ID を有効化）
resource "azurerm_container_app" "example" {
  name                = "example-container-app"
  resource_group_name = azurerm_resource_group.example.name

Shinichi-Nakagawa

resource "azurerm_container_app_environment" "uwa_container_app_environment" {
  name                = "uwa-container-app-env"
  resource_group_name = azurerm_resource_group.uwa_resource_group.name
  location            = azurerm_resource_group.uwa_resource_group.location
  internal_load_balancer_enabled = false
  infrastructure_subnet_id = azurerm_subnet.container_app_subnet.id
}

resource "azurerm_container_app" "uwa_container_app" {
  name                = "uwa-container-app"

Shinichi-Nakagawa

resource "azurerm_storage_account" "uwa_uwa_storage" {
  name                     = "uwa-uwastorageaccount"
  resource_group_name      = azurerm_resource_group.uwa_uwa_rg.name
  location                 = azurerm_resource_group.uwa_uwa_rg.location
  account_tier             = "Standard"
  account_replication_type = "LRS"
}

Shinichi-Nakagawa

terraform {
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~>3.0"
    }
  }

  required_version = ">= 0.14.9"
}

Shinichi-Nakagawa

terraform {
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~>3.0"
    }
  }

  required_version = ">= 0.14.9"
}

Shinichi-Nakagawa

Shinichi-Nakagawa

Shinichi-Nakagawa

"""
5. BigQuery読込
"""
from pyspark.sql import SparkSession
from pyspark.sql import DataFrame as SparkDataFrame
from pyspark.sql.utils import AnalysisException


# ここは同じ
spark: SparkSession = SparkSession \

Shinichi-Nakagawa

"""
1. Sessionを作る
"""

from pyspark.sql import SparkSession

# BigQueryを使う&Stringの範囲を広げる
spark: SparkSession = SparkSession \
    .builder \
    .appName(‘app_yakiu')\

Shinichi-Nakagawa

from datetime import datetime
import os

from pyspark.sql import SparkSession
from pyspark.sql import DataFrame as SparkDataFrame
from pyspark.sql.utils import AnalysisException
from pyspark.sql.types import StructType, StructField, DoubleType, DateType, StringType, LongType
spark = SparkSession \
.builder \
.appName('app_334')\