mysql数据库空间的influxDB增量统计

2020-08-25

业务系统中RDS的mysql的空间捉襟见肘时就会想起来需要做一下容量的统计和趋势监控实施的方案是：

定时用python从mysql的information_schema库中的TABLES表中抽取DATA_LENGTH+INDEX_LENGTH的数据以及DATA_FREE的数据来做统计项将数据抽取到influxDB中备查

核心的查询语句：

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        # 1048576 字节 等于 1MB
        # 监控门槛：
        # DATA_FREE>= 6MB （可优化空间大于6MB）
        # TABLE_ROWS>= 100k (10万行以上)
        # DATA_LENGTH>= 20MB (数据空间占用大于20MB)
        # INDEX_LENGTH>= 20MB (索引空间占用大于20MB)
        # `TABLE_SCHEMA` IN ('{"','".join(self.check_dbs)}')
        sql = f""" SELECT `TABLE_SCHEMA`,`TABLE_NAME`, CONCAT_WS('.',`TABLE_SCHEMA`,`TABLE_NAME`) AS DBTABLENAME,
(`DATA_FREE`/1048576) AS free_len_mb,
(`DATA_LENGTH`+ `INDEX_LENGTH`)/1048576 AS row_len_mb,
(`TABLE_ROWS`/1000) AS rows_kb ,
(`DATA_LENGTH`/1048576) AS dat_len_mb,
(`INDEX_LENGTH`/1048576) AS idx_len_mb
FROM `information_schema`.`TABLES` WHERE
`TABLE_SCHEMA` IN ('{"','".join(self.check_dbs)}')
AND (`DATA_FREE`>=6291456 OR TABLE_ROWS >= 100000 OR DATA_LENGTH>=20971520 OR INDEX_LENGTH>=15728640 )
ORDER BY free_len_mb DESC,row_len_mb DESC,dat_len_mb DESC,idx_len_mb DESC, `TABLE_SCHEMA` ASC,`TABLE_NAME` ASC
"""

然后单行的influxdb的表结构：

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    tsdb_item_record = {
        'measurement': 'dbtable_stats',
        'tags': {
            'db': db,
            'table':table,
            'dbtable':dbtable,
        },
        'time': f'{utcnow.strftime("%Y-%m-%dT%H:%M:%S")}Z',
        'fields': {
            'free_len_mb':free_len_mb,
            'row_len_mb':row_len_mb,
            'rows':rows_kb,
            'dat_len_mb':dat_len_mb,
            'idx_len_mb':idx_len_mb
        }
    }

这样在influxdb中我们就有了每个埋点间隔下统计的数据信息，接下来在grafana中可以用InfluxDB的查询函数统计出对应的信息并展示图表

按时间查询各个表的空间占用（数据+索引）的增长量：

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SELECT cumulative_sum(difference(mean("row_len_mb"))) FROM "dbspace_watches_rp"."dbtable_stats" WHERE $timeFilter GROUP BY time(5m), "dbtable" fill(null)

再加上一下查询起始时的值就是当下的总数据量的表数据空间排名：

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SELECT first("row_len_mb") + cumulative_sum(difference(mean("row_len_mb"))) FROM "dbspace_watches_rp"."dbtable_stats" WHERE $timeFilter GROUP BY time(5m), "dbtable" fill(null)

同理也可以得到库表的DATA_FREE也就是可优化空间的增长量和排名在此不再赘述另外提一句，mysql在做optmize释放空间的时候会锁表，所以还是在业务空闲期做这些释放空间的活比较好

另外可以顺便求一下倒数得到查询时间区间内的各表的增长率，方便发现特别高增长的表做对应的优化

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SELECT derivative(cumulative_sum(difference(mean("row_len_mb"))), 10m) FROM "dbspace_watches_rp"."dbtable_stats" WHERE $timeFilter GROUP BY time(1h), "dbtable" fill(null)

OpenCv开发中所遇到的问题备忘

2020-08-12

开发 python

1.qt库冲突的问题：

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You might be loading two sets of Qt binaries into the same process. Check that all plugins are compiled against the right Qt binaries. Export DYLD_PRINT_LIBRARIES=1 and check that only one set of binaries are being loaded.
QObject::moveToThread: Current thread (0x7ff56d74feb0) is not the object's thread (0x7ff570dfec60).
Cannot move to target thread (0x7ff56d74feb0)

运行conda环境下opencv时遇到的，查了一下大概是需要卸载了opencv-python后再安装一下opencv-python-headless的版本

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pip uninstall opencv-python
pip install opencv-python-headless

安装时长不够就用：

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pip install --default-timeout=50000  opencv-python-headless

参考： https://www.pythonheidong.com/blog/article/410902/

FastApi开发中所遇到的问题备忘

2020-08-12

开发 python

1. 需要fastapi的服务端提供静态文件：

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app.mount("/static", StaticFiles(directory=os.path.join(myapp.env().get_data_path(), 'static')), name="static")

其中第一个static是网站访问路径，第二个static是磁盘路径，第三个static是FastApi代码内部引用名称

2. 文件上传处理：

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async def file_upload(
         upfile: UploadFile = File(...)
):
    dest_file_path = 'uploaded/userfile.ext'
    destination = Path(dest_file_path)
    try:
        with destination.open("wb") as buffer:
            shutil.copyfileobj(upfile.file, buffer)
    finally:
        upload_file.file.close()

3. cors问题

服务端配置cros:

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origins = [
    #  "*"
    "https://localhost"
    , "http://localhost"
    , "http://localhost:8000"
    , "https://www.kumaxiong.com"
]
app.add_middleware(
    CORSMiddleware,
    allow_origins=origins,
    allow_credentials=True,
    allow_methods=["*"],
    # allow_methods=["DELETE", "GET", "POST", "PUT"],
    allow_headers=["*"],
)

客户端处理的时候不要with-credentials带上cookie等信息：

参考：https://blog.csdn.net/liyuling52011/article/details/80013725