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chmury_aronb/jupyter/UAM_1_avro.ipynb

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Init with first version
2021-04-24 15:54:14 +02:00
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1 Format danych AVRO\n",
"\n",
"Ćwiczenie ma na celu zademonstrowanie schematów danych AVRO, typów złożonych (mapy, listy, struktury zagnieżdżone) oraz wstęp do Glue / Athena\n",
"\n",
"## Przebieg ćwiczenia\n",
"* skonfiguruj środowisko uruchomieniowe Python (sugerowana Anaconda z Python 3)\n",
"* zainstaluj wszystkie wymagane biblioteki\n",
"\n",
"<code>\n",
"% conda create -n myenv python=3.8\n",
"% conda activate uam-datalake\n",
"% pip install -r ./datalake-uam/jupyter/requirements.txt\n",
"</code>\n",
"\n",
"* zaloguj się do konsoli AWS i stwórz Bucket testowy oraz bazę dancyh w Glue. Uzupełnij poniższy skrypt o te dane \n",
"* wygeneruj dane testowe w wybranym schemacie AVRO\n",
"* zapisz dane do plików na S3 w folderach s3:/<twoj-bukcet-name>/EventName/namespace=xxx/year=YYYY/month=MM/day=DD/version=VVV\n",
"* zarejestruj tabele w Glue z wykorzystaniem BOTO3 / crawler (poprzez konsole AWS GUI - przeglądarkę)\n",
"* skonfiguruj domyślną WorkGroup w Athena (PRIMARY) - konieczne wskazanie miejsce docelowego dla danych z zapytań (S3 location Athena) https://docs.aws.amazon.com/athena/latest/ug/getting-started.html\n",
"* sprawdź definicję tabeli i upewnij się że są zarejestrowane partycje (użyj polecenia MSCK REPAIR w Athena (LOAD PARTITIONS)\n",
"* sprawdź ile danych jest w tabeli (select count(*) from table) - Data Scanned in bytes\n",
"* odpytaj tabele z wykorzystaniem predykatu day=1 (partition elimination) - zweryfikuj ilość danych przeskanowanych (do porównania z ćwiczeniem 2 - parquet)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import boto3\n",
"\n",
"REGION = \"us-east-1\"\n",
"\n",
"\n",
"session_kwargs = {\n",
"\n",
" \"aws_access_key_id\":\"\",\n",
" \"aws_secret_access_key\":\"\",\n",
" \"aws_session_token\":\"\",\n",
" \"region_name\": REGION\n",
"}\n",
" \n",
"session = boto3.Session(**session_kwargs)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"from faker import Faker\n",
"from botocore.exceptions import ClientError\n",
"from avro.datafile import DataFileReader, DataFileWriter\n",
"from avro.io import DatumReader, DatumWriter\n",
"import time \n",
"import io\n",
"import datetime\n",
"from avro.schema import Parse\n",
"\n",
"\n",
"fake = Faker()\n",
"fake.seed_instance(4321)\n",
" \n",
"S3_BUCKET = \"datalake-dev-920628590621-us-east-1\"\n",
"\n",
"TEST_DB = 'datalake_dev_jk'\n",
"TEST_TABLE_NAME = 'avro_uam_test'\n",
"EVENT_NAME = \"UamTestEvent\"\n",
"\n",
"\n",
"s3_client = session.client(\"s3\")\n",
"glue_client = session.client(\"glue\")\n",
"\n",
"\n",
"def tear_down_test_db(database=TEST_DB):\n",
" db_names = [x[\"Name\"] for x in glue_client.get_databases()[\"DatabaseList\"] ]\n",
" if database in db_names:\n",
" glue_client.delete_database(Name=database)\n",
" print(\"{} deleted\".format(database))\n",
"\n",
" response_create_db = glue_client.create_database(DatabaseInput={'Name': database }) \n",
" print(\"%s db recreated\" % database)\n",
"\n",
"def tear_down_test_table(database=TEST_DB, table_name=TEST_TABLE_NAME):\n",
" tbl_list = [x[\"Name\"] for x in glue_client.get_tables(DatabaseName=database)[\"TableList\"]]\n",
" if table_name in tbl_list:\n",
" glue_client.delete_table(DatabaseName=database,Name=table_name)\n",
" print(\"test table {} deleted\".format(table_name))\n",
" else:\n",
" print(\"tbl %s not found\" % table_name)\n",
" \n",
"def tear_down_s3(bucket=S3_BUCKET,prefix=EVENT_NAME):\n",
" s3 = boto3.resource('s3',**session_kwargs)\n",
" bucket = s3.Bucket(bucket)\n",
" bucket.objects.filter(Prefix=prefix).delete()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. AVRO schema"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"UamTestEvent com.uam.datalake.v1 1.0.2\n"
]
},
{
"data": {
"text/plain": [
"{'mox-meta': {'version': '1.0.2', 'type': 'ENTITY_SNAPSHOT'},\n",
" 'namespace': 'com.uam.datalake.v1',\n",
" 'type': 'record',\n",
" 'name': 'UamTestEvent',\n",
" 'fields': [{'name': 'customerId',\n",
" 'type': {'type': 'string', 'avro.java.string': 'String'}},\n",
" {'name': 'isActive',\n",
" 'type': 'boolean',\n",
" 'doc': 'a boolean flag if the Customer is active'},\n",
" {'name': 'age', 'type': 'int'},\n",
" {'name': 'balance', 'type': 'float'},\n",
" {'name': 'accountBalance_logical_dec',\n",
" 'type': {'type': 'bytes',\n",
" 'logicalType': 'decimal',\n",
" 'precision': 20,\n",
" 'scale': 4}},\n",
" {'name': 'array_of_strings',\n",
" 'type': ['null',\n",
" {'type': 'array',\n",
" 'items': {'type': 'string', 'avro.java.string': 'String'}}],\n",
" 'default': None},\n",
" {'name': 'paymentDetails',\n",
" 'type': ['null',\n",
" {'type': 'record',\n",
" 'name': 'PaymentDetails',\n",
" 'fields': [{'name': 'counterPartyName',\n",
" 'type': ['null', {'type': 'string', 'avro.java.string': 'String'}],\n",
" 'default': None},\n",
" {'name': 'groupingId',\n",
" 'type': ['null', {'type': 'string', 'avro.java.string': 'String'}],\n",
" 'default': None},\n",
" {'name': 'payeeId',\n",
" 'type': ['null', {'type': 'string', 'avro.java.string': 'String'}],\n",
" 'default': None},\n",
" {'name': 'message',\n",
" 'type': ['null', {'type': 'string', 'avro.java.string': 'String'}],\n",
" 'default': None},\n",
" {'name': 'type',\n",
" 'type': {'type': 'enum',\n",
" 'name': 'PaymentType',\n",
" 'symbols': ['UNKNOWN', 'ONE', 'TWO']}},\n",
" {'name': 'otherAccountId',\n",
" 'type': ['null', {'type': 'string', 'avro.java.string': 'String'}],\n",
" 'default': None}]}],\n",
" 'default': None},\n",
" {'name': 'parameters',\n",
" 'type': ['null',\n",
" {'type': 'map',\n",
" 'avro.java.string': 'String',\n",
" 'values': {'type': 'string', 'avro.java.string': 'String'}}],\n",
" 'default': None}]}"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# test Avro Schema with all important cases\n",
"\n",
"1\n",
"\n",
"schema_string = \"\"\"\n",
"{\n",
" \"mox-meta\":{\n",
" \"version\":\"1.0.2\",\n",
" \"type\":\"ENTITY_SNAPSHOT\"\n",
" },\n",
" \"namespace\":\"com.uam.datalake.v1\",\n",
" \"type\":\"record\",\n",
" \"name\":\"\",\n",
" \"fields\":[\n",
" {\n",
" \"name\":\"customerId\",\n",
" \"type\":{\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" },\n",
" {\n",
" \"name\":\"isActive\",\n",
" \"type\":\"boolean\",\n",
" \"doc\":\"a boolean flag if the Customer is active\"\n",
" },\n",
" {\n",
" \"name\":\"age\",\n",
" \"type\":\"int\"\n",
" },\n",
" {\n",
" \"name\":\"balance\",\n",
" \"type\":\"float\"\n",
" },\n",
" {\n",
" \"name\":\"accountBalance_logical_dec\",\n",
" \"type\":{\n",
" \"type\":\"bytes\",\n",
" \"logicalType\":\"decimal\",\n",
" \"precision\":20,\n",
" \"scale\":4\n",
" }\n",
" },\n",
" {\n",
" \"name\":\"array_of_strings\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"array\",\n",
" \"items\":{\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" }\n",
" ],\n",
" \"default\":null\n",
" },\n",
" {\n",
" \"name\":\"paymentDetails\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"record\",\n",
" \"name\":\"PaymentDetails\",\n",
" \"fields\":[\n",
" {\n",
" \"name\":\"counterPartyName\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" ],\n",
" \"default\":null\n",
" },\n",
" {\n",
" \"name\":\"groupingId\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" ],\n",
" \"default\":null\n",
" },\n",
" {\n",
" \"name\":\"payeeId\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" ],\n",
" \"default\":null\n",
" },\n",
" {\n",
" \"name\":\"message\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" ],\n",
" \"default\":null\n",
" },\n",
" {\n",
" \"name\":\"type\",\n",
" \"type\":{\n",
" \"type\":\"enum\",\n",
" \"name\":\"PaymentType\",\n",
" \"symbols\":[\n",
" \"UNKNOWN\",\n",
" \"ONE\",\n",
" \"TWO\" \n",
" ]\n",
" }\n",
" },\n",
" {\n",
" \"name\":\"otherAccountId\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" ],\n",
" \"default\":null\n",
" }\n",
" ]\n",
" }\n",
" ],\n",
" \"default\":null\n",
" },\n",
" {\n",
" \"name\":\"parameters\",\n",
" \"type\":[\n",
" \"null\",\n",
" {\n",
" \"type\":\"map\",\n",
" \"avro.java.string\":\"String\",\n",
" \"values\":{\n",
" \"type\":\"string\",\n",
" \"avro.java.string\":\"String\"\n",
" }\n",
" }\n",
" ],\n",
" \"default\":null\n",
" }\n",
" ]\n",
"}\n",
"\"\"\"\n",
"\n",
"schema = json.loads(schema_string)\n",
"schema[\"name\"] = EVENT_NAME\n",
"\n",
"RECORD_NAME = schema[\"name\"]\n",
"NAMESPACE = schema[\"namespace\"]\n",
"VERSION = schema[\"mox-meta\"][\"version\"]\n",
"\n",
"print('%s %s %s' %(RECORD_NAME,NAMESPACE,VERSION))\n",
"schema"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Generating test data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# generate some avro data (buffer file) based on the above schema\n",
"\n",
"avro_schema = Parse(json.dumps(schema))\n",
"buf = io.BytesIO()\n",
"writer = DataFileWriter(buf, DatumWriter(), avro_schema)\n",
"\n",
"for x in range(0, 10000):\n",
"\n",
"\n",
" customer_id = fake.uuid4()\n",
" amount = fake.pydecimal(left_digits=8, right_digits=4)\n",
" amount_int = int(str(amount).replace('.', ''))\n",
"\n",
" strings_arrray = [fake.first_name() for x in range(0, fake.random.randint(1, 5))]\n",
"\n",
" paymentDetails = {'counterPartyName': customer_id,\n",
" 'groupingId': str(fake.uuid4()), 'payeeId': None, 'message': None,\n",
" 'type': 'ONE', 'otherAccountId': str(fake.uuid4())}\n",
" \n",
" randint = fake.random.randint(20, 70)\n",
" \n",
"\n",
" array_of_structs = [{\"field1\": \"one\"}, {\"field1\": \"two\"}]\n",
" customer = {\n",
" \"customerId\": customer_id,\n",
" \"isActive\": fake.random.choice([True, False]),\n",
" \"age\": randint,\n",
" \"balance\": fake.random.random() * 123,\n",
" \"accountBalance_logical_dec\": amount_int.to_bytes(amount_int.bit_length() // 8 + 1, byteorder='big',\n",
" signed=True),\n",
" \"array_of_strings\": strings_arrray,\n",
" \"paymentDetails\": paymentDetails,\n",
"\n",
" \"parameters\": {\"key1\": \"value1\", \"key2\": \"value2\"}\n",
"\n",
" }\n",
" writer.append(customer)\n",
"\n",
"\n",
"writer.flush()\n",
"raw_bytes = buf.getvalue()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=1/version=1.0.2/CustData_d6f44c22-5c87-4e14-956b-ad7d985226d0.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=2/version=1.0.2/CustData_cf0edf74-e76e-458f-a1d2-e092275a719c.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=3/version=1.0.2/CustData_f9ed4ad7-ed1c-4431-b9ab-317387cdb5af.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=4/version=1.0.2/CustData_d89b1c7f-66e3-4522-a603-1630abbf24fa.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=5/version=1.0.2/CustData_92483d0c-5254-4825-9bbb-59545fc6e4dd.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=6/version=1.0.2/CustData_3473649b-97c5-4597-965b-672a11cdad73.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=7/version=1.0.2/CustData_ecc999f8-eda7-4782-b844-17809980f34c.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=8/version=1.0.2/CustData_b95fd45c-8f0d-4612-8f8b-131437895013.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=9/version=1.0.2/CustData_5a5ef6ba-1576-4450-82a0-3f6f9a10a7c8.avro\n",
"uploaded UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=10/version=1.0.2/CustData_4e5dc9b8-6eb7-4fa4-93e0-61faf874b698.avro\n"
]
}
],
"source": [
"tear_down_s3()\n",
"\n",
"for i in range(1,11):\n",
"\n",
" target_key_name = '{record_name}/namespace={ns}/year=2020/month=2/day={day}/version={ver}/CustData_{rand}.avro'.format(\n",
" record_name=RECORD_NAME,ns=NAMESPACE, day=i,ver=VERSION, rand=fake.uuid4())\n",
" try:\n",
" response = s3_client.put_object(Body=raw_bytes, Bucket=S3_BUCKET, Key=target_key_name)\n",
" print(\"uploaded %s\" % target_key_name)\n",
" except ClientError as e:\n",
" logging.error(e)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Avro reading"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"UamTestEvent/namespace=com.uam.datalake.v1/year=2020/month=2/day=10/version=1.0.2/CustData_4e5dc9b8-6eb7-4fa4-93e0-61faf874b698.avro\n",
"{'customerId': 'cc733c92-6853-45f6-8e49-bec741188ebb', 'isActive': True, 'age': 58, 'balance': 49.34309768676758, 'accountBalance_logical_dec': b'7L\\xbc\\xff\\xf3', 'array_of_strings': ['Rebecca'], 'paymentDetails': {'counterPartyName': 'cc733c92-6853-45f6-8e49-bec741188ebb', 'groupingId': '9626bf79-2f97-4c0c-9aae-de080adab7df', 'payeeId': None, 'message': None, 'type': 'ONE', 'otherAccountId': '69261bc2-4a71-4de7-bc8b-1beb0d9320ac'}, 'parameters': {'key1': 'value1', 'key2': 'value2'}}\n"
]
}
],
"source": [
"print(target_key_name)\n",
"\n",
"obj = s3_client.get_object(Bucket=S3_BUCKET, Key=target_key_name)\n",
"record_raw = obj['Body'].read()\n",
"\n",
"\n",
"reader = DataFileReader(io.BytesIO(record_raw), DatumReader())\n",
"for line in reader:\n",
" print(line)\n",
" break\n",
"\n",
"avro_schema = reader.meta[\"avro.schema\"]\n",
"reader.close()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"b'{\"type\": \"record\", \"mox-meta\": {\"version\": \"1.0.2\", \"type\": \"ENTITY_SNAPSHOT\"}, \"name\": \"UamTestEvent\", \"namespace\": \"com.uam.datalake.v1\", \"fields\": [{\"type\": {\"type\": \"string\", \"avro.java.string\": \"String\"}, \"name\": \"customerId\"}, {\"type\": \"boolean\", \"name\": \"isActive\", \"doc\": \"a boolean flag if the Customer is active\"}, {\"type\": \"int\", \"name\": \"age\"}, {\"type\": \"float\", \"name\": \"balance\"}, {\"type\": {\"type\": \"bytes\", \"logicalType\": \"decimal\", \"precision\": 20, \"scale\": 4}, \"name\": \"accountBalance_logical_dec\"}, {\"type\": [\"null\", {\"type\": \"array\", \"items\": {\"type\": \"string\", \"avro.java.string\": \"String\"}}], \"name\": \"array_of_strings\", \"default\": null}, {\"type\": [\"null\", {\"type\": \"record\", \"name\": \"PaymentDetails\", \"namespace\": \"com.uam.datalake.v1\", \"fields\": [{\"type\": [\"null\", {\"type\": \"string\", \"avro.java.string\": \"String\"}], \"name\": \"counterPartyName\", \"default\": null}, {\"type\": [\"null\", {\"type\": \"string\", \"avro.java.string\": \"String\"}], \"name\": \"groupingId\", \"default\": null}, {\"type\": [\"null\", {\"type\": \"string\", \"avro.java.string\": \"String\"}], \"name\": \"payeeId\", \"default\": null}, {\"type\": [\"null\", {\"type\": \"string\", \"avro.java.string\": \"String\"}], \"name\": \"message\", \"default\": null}, {\"type\": {\"type\": \"enum\", \"name\": \"PaymentType\", \"namespace\": \"com.uam.datalake.v1\", \"symbols\": [\"UNKNOWN\", \"ONE\", \"TWO\"]}, \"name\": \"type\"}, {\"type\": [\"null\", {\"type\": \"string\", \"avro.java.string\": \"String\"}], \"name\": \"otherAccountId\", \"default\": null}]}], \"name\": \"paymentDetails\", \"default\": null}, {\"type\": [\"null\", {\"type\": \"map\", \"avro.java.string\": \"String\", \"values\": {\"type\": \"string\", \"avro.java.string\": \"String\"}}], \"name\": \"parameters\", \"default\": null}]}'"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"avro_schema"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tbl avro_uam_test not found\n"
]
},
{
"data": {
"text/plain": [
"{'ResponseMetadata': {'RequestId': '1d5a05a1-0253-436c-a85a-d21f334d51ae',\n",
" 'HTTPStatusCode': 200,\n",
" 'HTTPHeaders': {'date': 'Sat, 24 Apr 2021 11:20:04 GMT',\n",
" 'content-type': 'application/x-amz-json-1.1',\n",
" 'content-length': '2',\n",
" 'connection': 'keep-alive',\n",
" 'x-amzn-requestid': '1d5a05a1-0253-436c-a85a-d21f334d51ae'},\n",
" 'RetryAttempts': 0}}"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#register glue table with avro SCHEMA\n",
"tear_down_test_table() # create or replace\n",
"\n",
"glue_client.create_table(\n",
" DatabaseName=TEST_DB,\n",
" TableInput={\n",
" \"Name\" : TEST_TABLE_NAME,\n",
" 'Owner': 'owner',\n",
" 'StorageDescriptor': {\n",
" 'Columns': [\n",
" {'Name': 'customerId', 'Type': 'string'},\n",
" {'Name': 'isActive', 'Type': 'boolean'},\n",
" {'Name': 'age', 'Type': 'int'}, \n",
" {'Name': 'balance', 'Type': 'float'},\n",
" {'Name': 'accountBalance_logical_dec', 'Type': 'decimal(20,4)'},\n",
" {'Name': 'array_of_strings', 'Type': 'array<string>'},\n",
" {'Name': 'paymentdetails',\n",
" 'Type': 'struct<counterpartyname:string,groupingid:string,payeeid:string,message:string,type:string,otheraccountid:string>'},\n",
" {'Name': 'parameters', 'Type': 'map<string,string>'}\n",
" ],\n",
" 'Location': 's3://{}/{}/namespace={}/'.format(S3_BUCKET,RECORD_NAME,NAMESPACE),\n",
" 'InputFormat': 'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat',\n",
" 'OutputFormat': 'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat',\n",
" 'Compressed': False,\n",
" 'NumberOfBuckets': -1,\n",
" 'SerdeInfo': {\n",
" 'SerializationLibrary': 'org.apache.hadoop.hive.serde2.avro.AvroSerDe',\n",
" 'Parameters': \n",
" {\n",
" 'avro.schema.literal': json.dumps(schema),\n",
" 'serialization.format': '1'\n",
" }\n",
" },\n",
" 'BucketColumns': [],\n",
" 'SortColumns': [],\n",
" },\n",
" 'PartitionKeys': [\n",
" {'Name': 'year','Type': 'int'},\n",
" {'Name': 'month','Type': 'int'},\n",
" {'Name': 'day','Type': 'int'},\n",
" {'Name': 'version','Type': 'string'}\n",
" ],\n",
" 'TableType': 'EXTERNAL_TABLE', \n",
" 'Parameters': {\n",
" \n",
" 'avro.schema.literal': json.dumps(schema),\n",
" 'classification': 'avro',\n",
" 'compressionType': 'none',\n",
" \n",
" }\n",
" }\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### now you can find the table in Glue Data Catalogue and query with Athena (remember about partitions)\n",
"\n",
"```\n",
"SELECT * , paymentdetails.groupingid , \"$path\"\n",
"FROM \"avro_uam_test\" as a \n",
"CROSS JOIN UNNEST(array_of_strings) as t(names)\n",
"where customerid = '0d6f913f-9364-4898-875e-d07311d1e300' and day = 1\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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"pygments_lexer": "ipython3",
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