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compare-timeseries-database
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changed code to functions and add time execution benchmarks on CilickHouse

master
flashlan 3 years ago
parent
1a148971e9
commit
a48b8c43da
1 changed files with 301 additions and 257 deletions
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  1. 558
      compareDBs.ipynb

558
compareDBs.ipynb
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@ -47,25 +47,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 68, "execution_count": null,
"id": "ab6c6c81-6ac1-4668-a79b-a9a0341fb35a", "id": "ab6c6c81-6ac1-4668-a79b-a9a0341fb35a",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [ "outputs": [],
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"False"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"import configparser\n", "import configparser\n",
"import time\n",
"import timeit\n",
"from datetime import datetime\n", "from datetime import datetime\n",
"\n", "\n",
"import duckdb\n", "import duckdb\n",
@ -98,7 +89,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 42,
"id": "968403e3-2e5e-4834-b969-be4600e2963a", "id": "968403e3-2e5e-4834-b969-be4600e2963a",
"metadata": { "metadata": {
"tags": [] "tags": []
@ -138,19 +129,10 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"%%time\n", "# %%time\n",
"# Load Dataset\n", "# Load Dataset\n",
"df = pd.read_csv(\"out.csv\", index_col=0)" "df = pd.read_csv(\"out.csv\", index_col=0)\n",
] "df.head()"
},
{
"cell_type": "code",
"execution_count": null,
"id": "7e7c46b6-90ee-4ca3-8b5a-553b09ece913",
"metadata": {},
"outputs": [],
"source": [
"# df.head()"
] ]
}, },
{ {
@ -202,83 +184,287 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 44,
"id": "9cf86669-7722-4a2c-895c-51f0a5eebefc", "id": "c3202bbb-2655-45b2-b166-9f45a3ef854c",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"'Database created'"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"# !! O client oficial usa um driver http, nesse exemplo vamos usar a biblioteca\n", "# !! O client oficial usa um driver http, nesse exemplo vamos usar a biblioteca\n",
"# de terceirtos clickhouse_driver recomendada, por sua vez que usa tcp.\n", "# de terceirtos clickhouse_driver recomendada, por sua vez que usa tcp.\n",
"client = Client(\n", "def cHouseConnect():\n",
" host=ClickHouseUrl,\n", " client = Client(\n",
" user=ClickHouseUser,\n", " host=ClickHouseUrl,\n",
" password=ClickHouseKey,\n", " user=ClickHouseUser,\n",
" settings={\"use_numpy\": True},\n", " password=ClickHouseKey,\n",
")" " settings={\"use_numpy\": True},\n",
" )\n",
" return client\n",
"\n",
"\n",
"# Create Tables in ClickHouse\n",
"# !! ALTERAR TIPOS !!\n",
"# ENGINE: 'Memory' desaparece quando server é reiniciado\n",
"def cHouseCreateDb(databasename):\n",
" client = cHouseConnect()\n",
" client.execute(\n",
" \"CREATE TABLE IF NOT EXISTS {} (id UInt32,\"\n",
" \"from DateTime, at UInt64, to DateTime, open Float64,\"\n",
" \"close Float64, min Float64, max Float64, volume UInt32)\"\n",
" \"ENGINE MergeTree ORDER BY to\".format(databasename)\n",
" )\n",
" client.disconnect()\n",
" return \"Database created\"\n",
"\n",
"\n",
"# Write dataframe to db\n",
"def cHouseInsertDf(dbName, dataframe):\n",
" client = cHouseConnect()\n",
" client.insert_dataframe(\"INSERT INTO {} VALUES\".format(dbName), dataframe)\n",
" client.disconnect()\n",
" return \" dataframe {} inserted in clickhouse database\".format(dataframe)\n",
"\n",
"\n",
"def cHouseQueryDf(databaseName):\n",
" client = cHouseConnect()\n",
" dfQuery = client.query_dataframe(\n",
" \"SELECT * FROM default.{}\".format(databaseName)\n",
" ) # LIMIT 10000\n",
" client.disconnect()\n",
" return dfQuery\n",
"\n",
"\n",
"cHouseCreateDb(dbname)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 47,
"id": "a0a1f67b-2e63-462e-be66-d322d99837ea", "id": "cc4865b3-a1bc-4a35-9624-15334754b3a1",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"# Create Tables in ClickHouse\n", "# Insert to db and benchmark time\n",
"# !! ALTERAR TIPOS !!\n", "start = timeit.default_timer()\n",
"# ENGINE: 'Memory' desaparece quando server é reiniciado\n", "cHouseInsertDf(dbname, df)\n",
"client.execute(\n", "stop = timeit.default_timer()\n",
" \"CREATE TABLE IF NOT EXISTS {} (id UInt32,\"\n", "cHouse_write_execution_time = stop - start"
" \"from DateTime, at UInt64, to DateTime, open Float64,\"\n",
" \"close Float64, min Float64, max Float64, volume UInt32)\"\n",
" \"ENGINE MergeTree ORDER BY to\".format(dbname)\n",
")"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 48,
"id": "3a029a09-46f4-43c3-b3df-cfbed33fb0dc", "id": "1fac82c1-2d04-44ef-893a-dc13b755e6d8",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"%%time\n", "# read from db and benchmark time\n",
"# Write dataframe to db\n", "start = timeit.default_timer()\n",
"client.insert_dataframe(\"INSERT INTO {} VALUES\".format(dbname), df)" "dfCh = cHouseQueryDf(dbname)\n",
"stop = timeit.default_timer()\n",
"cHouse_read_execution_time = stop - start"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 49,
"id": "17251288-2442-43ee-98f2-ca680c3c4f13", "id": "597ae7bd-2eea-44d7-b379-f0eb7e745c15",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>from</th>\n",
" <th>at</th>\n",
" <th>to</th>\n",
" <th>open</th>\n",
" <th>close</th>\n",
" <th>min</th>\n",
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" <td>1.065995</td>\n",
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" <td>7730801</td>\n",
" <td>2023-01-02 15:58:45</td>\n",
" <td>1672675140000000000</td>\n",
" <td>2023-01-02 15:59:00</td>\n",
" <td>1.065995</td>\n",
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" <td>2023-01-02 15:59:00</td>\n",
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" <td>2023-01-02 15:59:15</td>\n",
" <td>1.066055</td>\n",
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" <td>1.066115</td>\n",
" <td>52</td>\n",
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" <td>7730803</td>\n",
" <td>2023-01-02 15:59:15</td>\n",
" <td>1672675170000000000</td>\n",
" <td>2023-01-02 15:59:30</td>\n",
" <td>1.066080</td>\n",
" <td>1.066025</td>\n",
" <td>1.066025</td>\n",
" <td>1.066110</td>\n",
" <td>57</td>\n",
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" id from at to \\\n",
"0 7730801 2023-01-02 15:58:45 1672675140000000000 2023-01-02 15:59:00 \n",
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"3 7730802 2023-01-02 15:59:00 1672675155000000000 2023-01-02 15:59:15 \n",
"4 7730803 2023-01-02 15:59:15 1672675170000000000 2023-01-02 15:59:30 \n",
"\n",
" open close min max volume \n",
"0 1.065995 1.066035 1.065930 1.066070 57 \n",
"1 1.065995 1.066035 1.065930 1.066070 57 \n",
"2 1.066055 1.066085 1.066005 1.066115 52 \n",
"3 1.066055 1.066085 1.066005 1.066115 52 \n",
"4 1.066080 1.066025 1.066025 1.066110 57 "
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"%%time\n", "dfCh.head()"
"client.query_dataframe(\"SELECT * FROM default.{}\".format(dbname)) # LIMIT 10000" ]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "86794e47-611f-4ca8-a7e8-07e71afafe67",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5.175396532999002\n"
]
}
],
"source": [
"print(cHouse_read_execution_time)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "e7926062-8e84-4d3f-90a9-32807ce4f3d4",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6.163630739996734\n"
]
}
],
"source": [
"print(cHouse_write_execution_time)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "51497522-bd6c-44a8-aaea-ec5dda30b95b", "id": "8faa5683-a204-461d-80c3-67644aa714ce",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"# %%time\n", "%%time\n",
"# df = pd.DataFrame(client.query_dataframe(\"SELECT * FROM default.{}\".format(dbname)))" "dfCh = cHouseQueryDf(dbname)"
] ]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
"id": "1d389546-911f-43f7-aad1-49f7bcc83503", "id": "1d389546-911f-43f7-aad1-49f7bcc83503",
"metadata": { "metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": [] "tags": []
}, },
"source": [ "source": [
@ -427,6 +613,14 @@
"conn.close()" "conn.close()"
] ]
}, },
{
"cell_type": "code",
"execution_count": null,
"id": "73de4294-1284-49b0-b31e-45db6e835877",
"metadata": {},
"outputs": [],
"source": []
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
@ -434,7 +628,36 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"# Read" "start = time.time()\n",
"# %%time\n",
"# Read\n",
"df = pd.read_sql_query('select * from \"comparedbs\"', con=engine)\n",
"end = time.time()\n",
"postgresql_read_time = exec_time(start, end)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6d1b7480-5bc7-4f08-8cf3-b9590802d8f7",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"print(postgresql_read_time)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6acb2959-3255-43bd-aea5-9ef70acc8902",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"df.head()"
] ]
}, },
{ {
@ -674,7 +897,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 69, "execution_count": null,
"id": "14f63810-1943-4e28-9bce-2148be6be02d", "id": "14f63810-1943-4e28-9bce-2148be6be02d",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -687,7 +910,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 70, "execution_count": null,
"id": "8ff6c090-7e02-435a-a179-f2aab81da972", "id": "8ff6c090-7e02-435a-a179-f2aab81da972",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -698,7 +921,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 71, "execution_count": null,
"id": "b4eb8ab9-81e8-4732-8cf7-51f0981d3d57", "id": "b4eb8ab9-81e8-4732-8cf7-51f0981d3d57",
"metadata": { "metadata": {
"tags": [] "tags": []
@ -712,19 +935,10 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 75, "execution_count": null,
"id": "97cb6b5b-65a5-46a0-a4ee-e5c535a716ab", "id": "97cb6b5b-65a5-46a0-a4ee-e5c535a716ab",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 925 ms, sys: 40 ms, total: 965 ms\n",
"Wall time: 1.43 s\n"
]
}
],
"source": [ "source": [
"%%time\n", "%%time\n",
"# send df to kd+ in memory bank\n", "# send df to kd+ in memory bank\n",
@ -733,21 +947,10 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 76, "execution_count": null,
"id": "c2ed2d51-bc8e-4207-892a-35fc55d43570", "id": "c2ed2d51-bc8e-4207-892a-35fc55d43570",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"data": {
"text/plain": [
"b':/home/sandman/q/tab1'"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"# write to on disk table\n", "# write to on disk table\n",
"q.sendSync(\"`:/home/sandman/q/tab1 set t\")" "q.sendSync(\"`:/home/sandman/q/tab1 set t\")"
@ -755,21 +958,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 77, "execution_count": null,
"id": "9c055a95-f73f-43a3-8fbd-61e42235117e", "id": "9c055a95-f73f-43a3-8fbd-61e42235117e",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1.94 ms, sys: 1 µs, total: 1.94 ms\n",
"Wall time: 426 ms\n"
]
}
],
"source": [ "source": [
"%%time\n", "%%time\n",
"# read from on disk table\n", "# read from on disk table\n",
@ -778,7 +972,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 78, "execution_count": null,
"id": "9760de38-9f04-4322-bfff-c7ee12d5dee5", "id": "9760de38-9f04-4322-bfff-c7ee12d5dee5",
"metadata": { "metadata": {
"tags": [] "tags": []
@ -790,21 +984,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 79, "execution_count": null,
"id": "c06c9222-c69d-4872-9d21-052281a013e2", "id": "c06c9222-c69d-4872-9d21-052281a013e2",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1.08 s, sys: 116 ms, total: 1.2 s\n",
"Wall time: 1.27 s\n"
]
}
],
"source": [ "source": [
"%%time\n", "%%time\n",
"# load to variable df2\n", "# load to variable df2\n",
@ -813,7 +998,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 80, "execution_count": null,
"id": "8815f01c-fd0a-4f94-ab7f-f8ede84ba4e7", "id": "8815f01c-fd0a-4f94-ab7f-f8ede84ba4e7",
"metadata": { "metadata": {
"tags": [] "tags": []
@ -825,144 +1010,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 82, "execution_count": null,
"id": "e6ed3927-4395-45cd-9a28-88c5db01f2e5", "id": "e6ed3927-4395-45cd-9a28-88c5db01f2e5",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1.25 s, sys: 132 ms, total: 1.39 s\n",
"Wall time: 1.46 s\n"
]
},
{
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" <td>1.066080</td>\n",
" <td>1.066025</td>\n",
" <td>1.066025</td>\n",
" <td>1.066110</td>\n",
" <td>57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>7730804</td>\n",
" <td>b'2023-01-02 15:59:30'</td>\n",
" <td>1672675185000000000</td>\n",
" <td>b'2023-01-02 15:59:45'</td>\n",
" <td>1.065980</td>\n",
" <td>1.065985</td>\n",
" <td>1.065885</td>\n",
" <td>1.066045</td>\n",
" <td>64</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>7730805</td>\n",
" <td>b'2023-01-02 15:59:45'</td>\n",
" <td>1672675200000000000</td>\n",
" <td>b'2023-01-02 16:00:00'</td>\n",
" <td>1.065975</td>\n",
" <td>1.066055</td>\n",
" <td>1.065830</td>\n",
" <td>1.066055</td>\n",
" <td>50</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 id from at \n",
"0 0 7730801 b'2023-01-02 15:58:45' 1672675140000000000 \\\n",
"1 1 7730802 b'2023-01-02 15:59:00' 1672675155000000000 \n",
"2 2 7730803 b'2023-01-02 15:59:15' 1672675170000000000 \n",
"3 3 7730804 b'2023-01-02 15:59:30' 1672675185000000000 \n",
"4 4 7730805 b'2023-01-02 15:59:45' 1672675200000000000 \n",
"\n",
" to open close min max volume \n",
"0 b'2023-01-02 15:59:00' 1.065995 1.066035 1.065930 1.066070 57 \n",
"1 b'2023-01-02 15:59:15' 1.066055 1.066085 1.066005 1.066115 52 \n",
"2 b'2023-01-02 15:59:30' 1.066080 1.066025 1.066025 1.066110 57 \n",
"3 b'2023-01-02 15:59:45' 1.065980 1.065985 1.065885 1.066045 64 \n",
"4 b'2023-01-02 16:00:00' 1.065975 1.066055 1.065830 1.066055 50 "
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"%%time\n", "%%time\n",
"# converto to dataframe\n", "# converto to dataframe\n",
@ -972,21 +1025,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 83, "execution_count": null,
"id": "0fc7f16b-6c39-4ebe-88d2-ff857e30ab62", "id": "0fc7f16b-6c39-4ebe-88d2-ff857e30ab62",
"metadata": { "metadata": {
"tags": [] "tags": []
}, },
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 1.11 s, sys: 116 ms, total: 1.23 s\n",
"Wall time: 1.3 s\n"
]
}
],
"source": [ "source": [
"%%time\n", "%%time\n",
"# select\n", "# select\n",
@ -995,7 +1039,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 84, "execution_count": null,
"id": "c88646ca-3d25-4a85-80b5-f9e559f568dd", "id": "c88646ca-3d25-4a85-80b5-f9e559f568dd",
"metadata": { "metadata": {
"tags": [] "tags": []

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