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…g-3000-allow-users-to-opt-out-of-data-snapshots-1
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,119 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "bc7d2d08", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import aqueduct as aq\n", | ||
| "from aqueduct.constants.enums import ArtifactType" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "9460bb78", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "client = aq.Client(api_key=\"\", aqueduct_address=\"\")\n", | ||
| "\n", | ||
| "\n", | ||
| "aq.global_config({'engine':'databricks_resource', 'lazy':True})" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "eb9e417e", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "#This is working with large data > 50GB.\n", | ||
| "snowflake_warehouse = client.resource('snowflake_resource')\n", | ||
| "hotel_reviews = snowflake_warehouse.sql('SELECT * FROM large_hotel_reviews;')" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "fa652f83", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "@aq.op(requirements=[])\n", | ||
| "def dummy(original_df, num_rows):\n", | ||
| " from pyspark.sql.functions import monotonically_increasing_id\n", | ||
| " from pyspark.sql.functions import rand\n", | ||
| " import math\n", | ||
| " \n", | ||
| " original_row_count = original_df.count()\n", | ||
| " num_partitions = int(math.ceil(num_rows / original_row_count))\n", | ||
| "\n", | ||
| " # Step 2: Repartition the DataFrame\n", | ||
| " replicated_df = original_df.repartition(num_partitions)\n", | ||
| "\n", | ||
| " # Step 3: Persist the DataFrame\n", | ||
| " replicated_df.persist()\n", | ||
| "\n", | ||
| " # Step 4: Duplicate the rows\n", | ||
| " while replicated_df.count() < num_rows:\n", | ||
| " replicated_df = replicated_df.union(replicated_df)\n", | ||
| "\n", | ||
| " print(replicated_df.count())\n", | ||
| "\n", | ||
| " return replicated_df\n", | ||
| "\n", | ||
| "generated_df = dummy(hotel_reviews, 10000000000)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "324fb630", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "snowflake_warehouse.save(generated_df, table_name=\"large_hotel_reviews\", update_mode=\"replace\")\n", | ||
| "\n", | ||
| "\n", | ||
| "client.publish_flow(\n", | ||
| " \"Creating_Large_Dataset\",\n", | ||
| " \"repartition hotel_reviews to create big dataset\",\n", | ||
| " artifacts=[generated_df],\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "7c9e16e2", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.8.8" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
178 changes: 178 additions & 0 deletions
178
examples/system-tests/Simple_Model_Medium_Data_K8s.ipynb
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,178 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "f6a9bd6c", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "num_rows = 10000000\n", | ||
| "DATA_SIZE_GB = 5\n", | ||
| "\n", | ||
| "flow_name = f\"Test {DATA_SIZE_GB}GB\"\n", | ||
| "print(\"Testing: \", flow_name)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "5ccef41d", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import aqueduct as aq\n", | ||
| "from aqueduct import op" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "d1d0d83e", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "address = \"http://localhost:8080\"\n", | ||
| "\n", | ||
| "api_key = aq.get_apikey()\n", | ||
| "client = aq.Client(api_key, address)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "8c78cdc9", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "aq.global_config({ \"engine\": \"k8s_2\" })" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "55db48ab", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "warehouse = client.resource(name=\"sf\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "14d8427b", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%%time\n", | ||
| "\n", | ||
| "d = warehouse.sql(f\"select * from LARGE_HOTEL_REVIEWS_STAGING_2041977877 LIMIT {num_rows}\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "86833b68", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%%time\n", | ||
| "\n", | ||
| "d.get()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "39d43c46", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "df = d.get()\n", | ||
| "\n", | ||
| "def actual_size():\n", | ||
| " size_bytes = df.memory_usage(deep=True).sum()\n", | ||
| " \n", | ||
| " # Convert bytes to gigabytes\n", | ||
| " size_gb = size_bytes / 1024**3\n", | ||
| " \n", | ||
| " return size_gb\n", | ||
| "\n", | ||
| "actual_size()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "704cf8fa", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "@op(\n", | ||
| " requirements=[]\n", | ||
| ")\n", | ||
| "def foo(df):\n", | ||
| " return df.head()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "27aa1787", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%%time\n", | ||
| "\n", | ||
| "out = foo(d)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "05c01f1c", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%%time\n", | ||
| "\n", | ||
| "client.publish_flow(flow_name, artifacts=[out])" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "c512d804", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3 (ipykernel)", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.10.10" | ||
| }, | ||
| "vscode": { | ||
| "interpreter": { | ||
| "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" | ||
| } | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1 +1,4 @@ | ||
| dist | ||
| node_modules/* | ||
| .parcel-cache/* | ||
| assets/* |
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|---|---|---|
| @@ -1,35 +1,38 @@ | ||
| // Source for this ESLint configuration: | ||
| // https://robertcooper.me/post/using-eslint-and-prettier-in-a-typescript-project | ||
| module.exports = { | ||
| parser: "@typescript-eslint/parser", | ||
| // Specifies the ESLint parser | ||
| parserOptions: { | ||
| ecmaVersion: 2020, | ||
| // Allows for the parsing of modern ECMAScript features | ||
| sourceType: "module", | ||
| // Allows for the use of imports | ||
| ecmaFeatures: { | ||
| jsx: true // Allows for the parsing of JSX | ||
| parser: '@typescript-eslint/parser', | ||
| // Specifies the ESLint parser | ||
| parserOptions: { | ||
| ecmaVersion: 2020, | ||
| // Allows for the parsing of modern ECMAScript features | ||
| sourceType: 'module', | ||
| // Allows for the use of imports | ||
| ecmaFeatures: { | ||
| jsx: true, // Allows for the parsing of JSX | ||
| }, | ||
| }, | ||
|
|
||
| } | ||
| }, | ||
| settings: { | ||
| react: { | ||
| version: "detect" // Tells eslint-plugin-react to automatically detect the version of React to use | ||
| settings: { | ||
| react: { | ||
| version: 'detect', // Tells eslint-plugin-react to automatically detect the version of React to use | ||
| }, | ||
| }, | ||
|
|
||
| } | ||
| }, | ||
| extends: ["plugin:react/recommended", "plugin:@typescript-eslint/recommended", "plugin:prettier/recommended"], | ||
| plugins: ['simple-import-sort', "unused-imports"], | ||
| rules: { | ||
| // Place to specify ESLint rules. Can be used to overwrite rules specified from the extended configs | ||
| // e.g. "@typescript-eslint/explicit-function-return-type": "off", | ||
| // Since we're using Typescript, checking prop-types is no longer needed. This line stops the prop-types errors from happening during lint. | ||
| 'react/prop-types': 0, | ||
| 'simple-import-sort/imports': 'error', | ||
| 'simple-import-sort/exports': 'error', | ||
| 'no-unused-vars': 'off', | ||
| 'unused-imports/no-unused-imports': 'error', | ||
| 'react/jsx-child-element-spacing': 'off' | ||
| } | ||
| extends: ['plugin:react/recommended', 'plugin:@typescript-eslint/recommended', 'plugin:prettier/recommended'], | ||
| plugins: ['simple-import-sort', 'unused-imports', 'react-hooks'], | ||
| rules: { | ||
| // Place to specify ESLint rules. Can be used to overwrite rules specified from the extended configs | ||
| // e.g. "@typescript-eslint/explicit-function-return-type": "off", | ||
| // Since we're using Typescript, checking prop-types is no longer needed. This line stops the prop-types errors from happening during lint. | ||
| 'react/prop-types': 0, | ||
| 'simple-import-sort/imports': 'error', | ||
| 'simple-import-sort/exports': 'error', | ||
| 'no-unused-vars': 'off', | ||
| 'unused-imports/no-unused-imports': 'error', | ||
| 'react/jsx-child-element-spacing': 'off', | ||
| 'react-hooks/rules-of-hooks': 'error', | ||
| // Checks rules of Hooks | ||
| 'react-hooks/exhaustive-deps': 'warn', // Checks effect dependencies | ||
| }, | ||
| }; |
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