创建“区分类目的向量表” 失败

[sunwsh]

测试环境是 按照 单机模式部署的havenask。

创建全量表：
/ha3_install/hape create table -t in_offline_category_vec3 -s /ha3_install/example/cases/vector/category_vector1.json -p 1 -f /ha3_install/example/data/vector_category.data -c /ha3_install/hape_conf/vector

schema 文件(category_vector1.json) ，帮忙看看这个配置有错吗？ 有没有方法检查 schema 文件 是否有错？

{
    "columns": [
        {
            "name": "id",
            "type": "UINT32"
        },
        {
            "name": "category",
            "type": "UINT32"
        },
        {
            "name": "vector",
            "type": "STRING"
        },
        {
            "name": "DUP_vector",
            "type": "RAW"
        }
    ],
    "indexes": [
            {
            "name": "id",
            "index_config" : {
                "index_fields": [
                    {
                        "field_name": "id"
                    }
                ]
            },
            "index_type": "PRIMARY_KEY64"
        },
        {
            "name": "id",
            "index_config" : {
                "index_fields": [
                    {
                        "field_name": "id"
                    }
                ]
            },
            "index_type": "ATTRIBUTE"
        },
        {
            "name": "category",
            "index_config" : {
                "index_fields": [
                    {
                        "field_name": "category"
                    }
                ]
            },
            "index_type": "ATTRIBUTE"
        },
        {
            "name": "vector",
            "index_config" : {
                "index_fields": [
                    {
                        "field_name": "vector"
                    }
                ]
            },
            "index_type": "ATTRIBUTE"
        },
        {
            "name": "vector_index",
            "index_type": "ANN",
            "index_config": {
                "index_fields": [
                    {
                        "boost": 1,
                        "field_name": "id"
                    },
                    {
                        "boost": 1,
                        "field_name": "category"
                    },
                    {
                        "boost": 1,
                        "field_name": "DUP_vector"
                    }
                ],
                "index_params": {
                    "indexer": "aitheta2_indexer",
                    "parameters": "{\"enable_rt_build\":\"true\",\"min_scan_doc_cnt\":\"20000\",\"vector_index_type\":\"Qc\",\"major_order\":\"col\",\"builder_name\":\"QcBuilder\",\"distance_type\":\"SquaredEuclidean\",\"embedding_delimiter\":\",\",\"enable_recall_report\":\"true\",\"is_embedding_saved\":\"true\",\"linear_build_threshold\":\"5000\",\"dimension\":\"128\",\"search_index_params\":\"{\\\"proxima.qc.searcher.scan_ratio\\\":0.01}\",\"searcher_name\":\"QcSearcher\",\"build_index_params\":\"{\\\"proxima.qc.builder.quantizer_class\\\":\\\"Int8QuantizerConverter\\\",\\\"proxima.qc.builder.quantize_by_centroid\\\":true,\\\"proxima.qc.builder.optimizer_class\\\":\\\"BruteForceBuilder\\\",\\\"proxima.qc.builder.thread_count\\\":10,\\\"proxima.qc.builder.optimizer_params\\\":{\\\"proxima.linear.builder.column_major_order\\\":true},\\\"proxima.qc.builder.store_original_features\\\":false,\\\"proxima.qc.builder.train_sample_count\\\":3000000,\\\"proxima.qc.builder.train_sample_ratio\\\":0.5}\"}"
                }
            }

        },
        {
            "name": "summary",
            "index_type": "SUMMARY",
            "index_config": {
                "index_fields": [
                    {
                        "field_name": "id"
                    },
                    {
                        "field_name": "category"
                    },
                    {
                        "field_name": "vector"
                    }
                ]
            }       
        }
        
    ]
}

vector_category.data 文件, 每行结尾(1F0A))

CMD=add
id=1
vector=0.57350874,0.20913178,-0.28007376,-0.008224763,0.032035876,-0.06109254,0.016208794,0.2546715,-0.5938332,0.2194785,-0.603397,0.095939286,-0.4343296,0.29292983,0.19570276,0.07006806,0.4219676,0.008796717,-0.1956801,0.10365201,-0.18756211,-0.1959297,-0.64994687,-0.0043594907,-0.12155021,-0.37211925,-0.033330534,0.37927315,0.14685613,0.14631498,0.2263155,0.020013737,-0.48688003,0.38279092,-0.14551091,-0.14309452,0.0836372,-0.2602252,-0.68886805,-0.18670991,0.026953692,-0.1361577,0.54825664,0.5495113,-0.11404511,0.020755235,-0.3592109,0.35327643,-0.17384957,0.06951289,-0.33219633,0.32536888,0.4178303,0.06838637,-0.32600296,-0.39717215,0.37040582,0.2577843,-0.022891786,-0.19590716,-0.34784496,0.45056996,-0.16618372,-0.048093718,-0.4501398,0.16741453,0.0021240758,-0.22811683,-0.30895764,-0.29165566,0.51220524,0.26545066,-0.46743664,-0.18925984,0.11317849,0.01674415,-0.41176468,-0.41503182,-0.52814317,-0.52559006,0.5788051,0.12608618,0.62300944,0.20152776,-0.39167175,0.099368036,0.34757188,-0.2860248,0.47917366,0.44290003,-0.3663736,0.074007034,-0.44493687,0.5212625,0.5742631,0.06809457,0.20434684,-0.2527957,0.08273791,-0.5062737,0.30677673,0.0037546167,0.53646725,0.6939553,-0.19357872,0.62397563,-0.25602227,-0.73345435,0.23730282,-0.11466419,-0.22964483,-0.18373214,-0.28414255,0.67296755,0.38798898,-0.0795316,0.050292946,0.51636153,-0.3399461,0.14268692,-0.5273593,-0.055386372,-0.29121432,-0.36689624,0.762627,0.14242941,0.14173277,0.08323621
category=1