videx_build_env.py error

[xiamachun]

Environment Setup

videx version: git 拉最新的
mysql version: percona 8.0.34-26
deployment: plugin
os:Debian 12

Observed vs Expected Behavior

https://github.com/bytedance/videx/blob/main/doc/installation_zh.md -按照这个文档里面的编译完整的 MySQL Server (包含 VIDEX 引擎) 。
编译阶段一切正常，初始化的时候报下面的错误，麻烦看下：
似乎跟histogram min,max value 排序相关
(videx_py39) root@xxxxx:~/videx_server# python src/sub_platforms/sql_opt/videx/scripts/videx_build_env.py --target 127.0.0.1:13308:tpch_tiny:videx:password --videx 127.0.0.1:13308:videx_tpch_tiny:videx:password
logging config: {'version': 1, 'formatters': {'default': {'format': '%(asctime)s [%(process)d:%(thread)d] %(levelname)-8s %(name)-15s [%(filename)s:%(lineno)d] %(_videx_trace_id)s %(message)s', 'datefmt': '%Y-%m-%d %H:%M:%S'}}, 'filters': {'videx_trace_filter': {'()': <class 'sub_platforms.sql_opt.videx.videx_logging.VidexTraceIdFilter'>}}, 'handlers': {'console': {'class': 'logging.StreamHandler', 'formatter': 'default', 'level': 'INFO', 'stream': 'ext://sys.stdout', 'filters': ['videx_trace_filter']}, 'info_log_file': {'class': 'logging.handlers.RotatingFileHandler', 'formatter': 'default', 'filename': './log/videx_app_info.log', 'maxBytes': 100000000, 'backupCount': 5, 'filters': ['videx_trace_filter']}, 'error_log_file': {'class': 'logging.handlers.RotatingFileHandler', 'formatter': 'default', 'filename': './log/videx_app_error.log', 'maxBytes': 100000000, 'backupCount': 5, 'filters': ['videx_trace_filter']}}, 'root': {'level': 'NOTSET', 'handlers': ['console', 'info_log_file'], 'propagate': False}, 'loggers': {'error_logger': {'level': 'ERROR', 'handlers': ['error_log_file'], 'propagate': True}}}
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_build_env.py:154] - metadata file is None
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:608] - fetch_all_meta_for_videx. target_db='tpch_tiny' result_dir='temp_meta_1763972875' n_buckets=16 hist_force=True hist_mem_size=200000000 all_table_names=None hist_algo=None
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:633] - fetch meta for videx: ndv_single_file = 'videx_tpch_tiny_ndv_single.json' not found in result_dir = 'temp_meta_1763972875', or exist ndv single is not enough.fetch it: sorted(ndv_single_dict.keys()) = [] miss_ndv_tables=['customer', 'lineitem', 'nation', 'orders', 'part', 'partsupp', 'region', 'supplier']
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_ACCTBAL [0/8]: SELECT COUNT(DISTINCT C_ACCTBAL) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_ADDRESS [1/8]: SELECT COUNT(DISTINCT C_ADDRESS) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_COMMENT [2/8]: SELECT COUNT(DISTINCT C_COMMENT) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_CUSTKEY [3/8]: SELECT COUNT(DISTINCT C_CUSTKEY) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_MKTSEGMENT [4/8]: SELECT COUNT(DISTINCT C_MKTSEGMENT) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_NAME [5/8]: SELECT COUNT(DISTINCT C_NAME) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_NATIONKEY [6/8]: SELECT COUNT(DISTINCT C_NATIONKEY) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for customer.tpch_tiny.customer.C_PHONE [7/8]: SELECT COUNT(DISTINCT C_PHONE) FROM tpch_tiny.customer;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_COMMENT [0/17]: SELECT COUNT(DISTINCT L_COMMENT) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_COMMITDATE [1/17]: SELECT COUNT(DISTINCT L_COMMITDATE) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_DISCOUNT [2/17]: SELECT COUNT(DISTINCT L_DISCOUNT) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_EXTENDEDPRICE [3/17]: SELECT COUNT(DISTINCT L_EXTENDEDPRICE) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_ID [4/17]: SELECT COUNT(DISTINCT L_ID) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_LINENUMBER [5/17]: SELECT COUNT(DISTINCT L_LINENUMBER) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_LINESTATUS [6/17]: SELECT COUNT(DISTINCT L_LINESTATUS) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_ORDERKEY [7/17]: SELECT COUNT(DISTINCT L_ORDERKEY) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_PARTKEY [8/17]: SELECT COUNT(DISTINCT L_PARTKEY) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_QUANTITY [9/17]: SELECT COUNT(DISTINCT L_QUANTITY) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_RECEIPTDATE [10/17]: SELECT COUNT(DISTINCT L_RECEIPTDATE) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_RETURNFLAG [11/17]: SELECT COUNT(DISTINCT L_RETURNFLAG) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_SHIPDATE [12/17]: SELECT COUNT(DISTINCT L_SHIPDATE) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_SHIPINSTRUCT [13/17]: SELECT COUNT(DISTINCT L_SHIPINSTRUCT) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_SHIPMODE [14/17]: SELECT COUNT(DISTINCT L_SHIPMODE) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_SUPPKEY [15/17]: SELECT COUNT(DISTINCT L_SUPPKEY) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for lineitem.tpch_tiny.lineitem.L_TAX [16/17]: SELECT COUNT(DISTINCT L_TAX) FROM tpch_tiny.lineitem;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for nation.tpch_tiny.nation.N_COMMENT [0/4]: SELECT COUNT(DISTINCT N_COMMENT) FROM tpch_tiny.nation;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for nation.tpch_tiny.nation.N_NAME [1/4]: SELECT COUNT(DISTINCT N_NAME) FROM tpch_tiny.nation;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for nation.tpch_tiny.nation.N_NATIONKEY [2/4]: SELECT COUNT(DISTINCT N_NATIONKEY) FROM tpch_tiny.nation;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for nation.tpch_tiny.nation.N_REGIONKEY [3/4]: SELECT COUNT(DISTINCT N_REGIONKEY) FROM tpch_tiny.nation;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_CLERK [0/9]: SELECT COUNT(DISTINCT O_CLERK) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_COMMENT [1/9]: SELECT COUNT(DISTINCT O_COMMENT) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_CUSTKEY [2/9]: SELECT COUNT(DISTINCT O_CUSTKEY) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_ORDERDATE [3/9]: SELECT COUNT(DISTINCT O_ORDERDATE) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_ORDERKEY [4/9]: SELECT COUNT(DISTINCT O_ORDERKEY) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_ORDERPRIORITY [5/9]: SELECT COUNT(DISTINCT O_ORDERPRIORITY) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_ORDERSTATUS [6/9]: SELECT COUNT(DISTINCT O_ORDERSTATUS) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_SHIPPRIORITY [7/9]: SELECT COUNT(DISTINCT O_SHIPPRIORITY) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for orders.tpch_tiny.orders.O_TOTALPRICE [8/9]: SELECT COUNT(DISTINCT O_TOTALPRICE) FROM tpch_tiny.orders;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_BRAND [0/9]: SELECT COUNT(DISTINCT P_BRAND) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_COMMENT [1/9]: SELECT COUNT(DISTINCT P_COMMENT) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_CONTAINER [2/9]: SELECT COUNT(DISTINCT P_CONTAINER) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_MFGR [3/9]: SELECT COUNT(DISTINCT P_MFGR) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_NAME [4/9]: SELECT COUNT(DISTINCT P_NAME) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_PARTKEY [5/9]: SELECT COUNT(DISTINCT P_PARTKEY) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_RETAILPRICE [6/9]: SELECT COUNT(DISTINCT P_RETAILPRICE) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_SIZE [7/9]: SELECT COUNT(DISTINCT P_SIZE) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for part.tpch_tiny.part.P_TYPE [8/9]: SELECT COUNT(DISTINCT P_TYPE) FROM tpch_tiny.part;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for partsupp.tpch_tiny.partsupp.PS_AVAILQTY [0/6]: SELECT COUNT(DISTINCT PS_AVAILQTY) FROM tpch_tiny.partsupp;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for partsupp.tpch_tiny.partsupp.PS_COMMENT [1/6]: SELECT COUNT(DISTINCT PS_COMMENT) FROM tpch_tiny.partsupp;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for partsupp.tpch_tiny.partsupp.PS_ID [2/6]: SELECT COUNT(DISTINCT PS_ID) FROM tpch_tiny.partsupp;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for partsupp.tpch_tiny.partsupp.PS_PARTKEY [3/6]: SELECT COUNT(DISTINCT PS_PARTKEY) FROM tpch_tiny.partsupp;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for partsupp.tpch_tiny.partsupp.PS_SUPPKEY [4/6]: SELECT COUNT(DISTINCT PS_SUPPKEY) FROM tpch_tiny.partsupp;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for partsupp.tpch_tiny.partsupp.PS_SUPPLYCOST [5/6]: SELECT COUNT(DISTINCT PS_SUPPLYCOST) FROM tpch_tiny.partsupp;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for region.tpch_tiny.region.R_COMMENT [0/3]: SELECT COUNT(DISTINCT R_COMMENT) FROM tpch_tiny.region;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for region.tpch_tiny.region.R_NAME [1/3]: SELECT COUNT(DISTINCT R_NAME) FROM tpch_tiny.region;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for region.tpch_tiny.region.R_REGIONKEY [2/3]: SELECT COUNT(DISTINCT R_REGIONKEY) FROM tpch_tiny.region;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_ACCTBAL [0/7]: SELECT COUNT(DISTINCT S_ACCTBAL) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_ADDRESS [1/7]: SELECT COUNT(DISTINCT S_ADDRESS) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_COMMENT [2/7]: SELECT COUNT(DISTINCT S_COMMENT) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_NAME [3/7]: SELECT COUNT(DISTINCT S_NAME) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_NATIONKEY [4/7]: SELECT COUNT(DISTINCT S_NATIONKEY) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_PHONE [5/7]: SELECT COUNT(DISTINCT S_PHONE) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:417] - fetch NDV for supplier.tpch_tiny.supplier.S_SUPPKEY [6/7]: SELECT COUNT(DISTINCT S_SUPPKEY) FROM tpch_tiny.supplier;
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_metadata.py:655] - fetch meta for videx: hist_file='videx_tpch_tiny_histogram.json' not found in result_dir='temp_meta_1763972875', or exist hist is not enough.fetch it. sorted(hist_dict.keys())=[] miss_hist_tables=['customer', 'lineitem', 'nation', 'orders', 'part', 'partsupp', 'region', 'supplier']
2025-11-24 16:27:55 [46227:139813563590464] WARNING root [db_variable.py:79] - version not updated, return empty str
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_histogram.py:1317] - Generating Histogram for tpch_tiny.customer.C_ACCTBAL with 16 n_buckets
2025-11-24 16:27:55 [46227:139813563590464] INFO root [videx_histogram.py:1317] - Generating Histogram for tpch_tiny.customer.C_ADDRESS with 16 n_buckets
Traceback (most recent call last):
File "/root/videx_server/src/sub_platforms/sql_opt/videx/scripts/videx_build_env.py", line 164, in
files = fetch_all_meta_with_one_file(meta_path=meta_path,
File "/root/videx_server/src/sub_platforms/sql_opt/videx/videx_metadata.py", line 762, in fetch_all_meta_with_one_file
stats_dict, hist_dict, ndv_single_dict, ndv_mulcol_dict = fetch_all_meta_for_videx(
File "/root/videx_server/src/sub_platforms/sql_opt/videx/videx_metadata.py", line 657, in fetch_all_meta_for_videx
tmp_hist_dict = generate_fetch_histogram(env, target_db, miss_hist_tables,
File "/root/videx_server/src/sub_platforms/sql_opt/videx/videx_histogram.py", line 1323, in generate_fetch_histogram
hist = fetch_col_histogram(env, target_db, table_name, col.name, n_buckets, force=force,
File "/root/videx_server/src/sub_platforms/sql_opt/videx/videx_histogram.py", line 1153, in fetch_col_histogram
return query_histogram(env, dbname, table_name, col_name)
File "/root/videx_server/src/sub_platforms/sql_opt/videx/videx_histogram.py", line 561, in query_histogram
return HistogramStats.init_from_mysql_json(data=hist_dict)
File "/root/videx_server/src/sub_platforms/sql_opt/videx/videx_histogram.py", line 458, in init_from_mysql_json
return HistogramStats(
File "/root/miniconda3/envs/videx_py39/lib/python3.9/site-packages/pydantic/main.py", line 214, in init
validated_self = self.pydantic_validator.validate_python(data, self_instance=self)
pydantic_core._pydantic_core.ValidationError: 1 validation error for HistogramStats
Value error, Buckets must have monotonically increasing, but got buckets=[HistogramBucket(min_value=' XO4xLzCAHLmvS4', max_value='2GTz XxGSbkAp8bKVjRajsxDXo', cum_freq=0.0627831715210356, row_count=97.0, size=0, bucket_freq=0.0627831715210356), HistogramBucket(min_value='2Ix5exZPldc bbvG49aMtmCkuAkTESsKz5nQaWHP', max_value='5xsAvgyKzy3o8o', cum_freq=0.1255663430420712, row_count=97.0, size=0, bucket_freq=0.0627831715210356), HistogramBucket(min_value='5y0xp60PiGcY3mpI7RDLVqwsRLxU5', max_value='A1IwcCJQfwD2yBvVjuQ,1 YF', cum_freq=0.1883495145631068, row_count=97.0, size=0, bucket_freq=0.0627831715210356), HistogramBucket(min_value='a2P82chwooKhZ1bZwx9Orvo0aHXxvFpn5', max_value='BsW4757envOGxVaTILzfsBreT8OaNlZvPMEUxP', cum_freq=0.2511326860841424, row_count=97.0, size=0, bucket_freq=0.0627831715210356), HistogramBucket(min_value='Bt95 UHUS35JSh', max_value='DzPwU5gS9q70sck6htdexoN0L1u1Ku4hJ', cum_freq=0.313915857605178, row_count=97.0, size=0, bucket_freq=0.06278317152103557), HistogramBucket(min_value='dZVg,73zJP9c5RG9', max_value='fva5m96f5BkLk,D, qzd', cum_freq=0.3766990291262136, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='FwSeoIwtjDPoRFevqHLmjJtvdFkAR16yh3Ao', max_value='I2n74 X4PDoyWZ3wh', cum_freq=0.4394822006472492, row_count=97.0, size=0, bucket_freq=0.06278317152103557), HistogramBucket(min_value='i2s86YanVhkSUqQvfHhHsIlUpB2cPwT5V5E96s', max_value='jwxN9nJBXN', cum_freq=0.5022653721682848, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='jXEiHRQm4nXzkaUfgCt53rmKzSRnEC', max_value='m,KoHb2zynI3euMkYGYRFXMy1', cum_freq=0.5650485436893203, row_count=97.0, size=0, bucket_freq=0.06278317152103552), HistogramBucket(min_value='m0B335hwM UXxg4byW3hqm9', max_value='NTq5fPFMnopHwPbcJCQag gi7qMtXbLPlJOMcdAe', cum_freq=0.627831715210356, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='NtYOVyClizxjYF L3d9dC6g', max_value='PuA,dO,VbQBg5Nd', cum_freq=0.6906148867313916, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='puSAnm cbptVohbwEsA3 mk6v91JaPV6GVF6Zxem', max_value='RWTu3tyCU NN5', cum_freq=0.7533980582524272, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='s1gd1XrAFZyz9dxgOe84DLLB', max_value='TZfJKs,5Cq42jmgo3,vf8LdCo5PncyBcF1vxbgLH', cum_freq=0.8161812297734627, row_count=97.0, size=0, bucket_freq=0.06278317152103552), HistogramBucket(min_value='u TLg5uInljo', max_value='VrJpGNJvMLfIQ3m7DTcaBkE', cum_freq=0.8789644012944984, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='VsiXQqGyhGlePEbq1thi2QqsALEr9auaIXNd', max_value='xzyrNijsfuqj8hEeyvrhHCfRaMBY,FNyeb3HWd', cum_freq=0.941747572815534, row_count=97.0, size=0, bucket_freq=0.06278317152103563), HistogramBucket(min_value='y,Fen5BgXdn4ZEbl5CFV ,AYbToj4sqgD,IVRG', max_value='zza5OQxXmhC5mMwI4qvZ2,6TEyQfNdIcMs6n7YW', cum_freq=1.0, row_count=90.0, size=0, bucket_freq=0.058252427184465994)] data_type='string' histogram_type='equi-height' null_values=0.0 collation_id=255 last_updated='2025-11-24 08:27:56.003349' sampling_rate=1.0 number_of_buckets_specified=16 database_type=None [type=value_error, input_value={'buckets': [HistogramBuc..., 'database_type': None}, input_type=dict]
For further information visit https://errors.pydantic.dev/2.10/v/value_error

[kr11]

Hi @xiamachun

I was notified that the email might have failed to send, so I’m answering your questions here instead.

1. About the Docker build errors
   We’ve seen both issues you opened. Another contributor @YoungHypo and I are working on them, and we expect to have them fixed within this week.
   Our preliminary investigation shows this was caused by the recent update on VIEDX for MariaDB . The regression tests were not thorough enough, which unintentionally affected existing functionality. We’re very sorry about that.
   We’ve already opened a PR [CI] Recover the Basic CI Pipeline for VIDEX testing #75 , and will be adding CI/CD tests soon.

2. About MySQL 8.0.42
   Please refer to PR [Compatibility] MySQL 8.0.42 #17 , i.e., switch to the compatibility/mysql8.0.42 branch.
   From that branch, copy src/mysql/videx into your MySQL source tree and try compiling again.
   We found that 8.0.42 has some minor interface changes compared with 8.0.34. Switching to this branch should allow the build to succeed.

3. About real-world usage
   As mentioned in the README, the default open‑sourced statistics collection method is highly accurate, but it puts relatively high load on the original database.
   Index recommendation services of both ByteDance Inside and Volcano Engine are based on VIDEX.
   Internally we have a lightweight sampling solution, but we currently don’t have the bandwidth to open‑source and migrate that part. If you’re interested, we can open an issue and share the technical design there.

4. About the logs and follow‑up
   Since the email contained a lot of log output, I might have missed some key details. If I did, please forgive the oversight and feel free to follow up with more questions. For future email exchanges, you can put large log chunks into attachments—this will make it easier for us to communicate.

[xiamachun]

thanks a lot Kangrong.
for MySQL 8.0.42 ,it works for branch compatibility/mysql8.0.42 and build successfully.
but it hangs on post videx metadata to 127.0.0.1:5001

when i try to login with another session,it hangs by opening tables

any ideas?