If no data is found when you call the Search operation for search indexes, data may not be correctly synchronized from the data table to the search index or you used an inappropriate query method. In this case, check whether the data is correctly synchronized from the data table to the search index and whether you used an appropriate query method.
Problem description
When I call the Search operation for search indexes to query data, no data is found.
Possible causes
Cause 1: Data in the data table is incorrectly synchronized to the search index
Case 1: Data in the data table is not synchronized to the search index. Data in the data table is asynchronously synchronized to the search index. In this case, data in the search index may not be updated.
Case 2: Column names in the search index are case-sensitive and may not match the column names in the data table. For example, a column in the data table is named ColumnName. If the column in the search index is named columnname, columnname does not match the column name in the data table.
Case 3: The data type of a column in the search index does not match the data type of the mapped column in the data table. For example, a column in the data table is of the Integer type but the mapped column in the search index is of the Keyword type.
NoteThe Wide column model of Tablestore is schema-free. An attribute column can have different data types in different rows, which may cause the synchronization from the data table to the search index to fail for specific rows.
Case 4: The data type of a column in the search index does not match the data format of the mapped column in the data table. For example, a column in the data table is of the String data type and has a value of
-91,100
, but the mapped column in the search index is of the Geopoint, Nested, or Vector data type.NoteThe Geopoint data type in the search index is in the
latitude,longitude
format. The latitude must be in the range of -90 to +90, and the longitude must be in the range of -180 to +180. The latitude must be specified before the longitude.The Nested data type in the search index is in the JSON array format. Example:
[{"tagName":"tag1", "score":0.8}, {"tagName":"tag2", "score":0.2}]
.The Vector data type in the search index is in the Float32 array format. The length of the array must be the same as the number of dimensions of the field. For example, the number of dimensions for
[1,5.1,4.7,0.08]
is 4.
Cause 2: An inappropriate query method is used
Case 1: Match query is used to query data in fields of the Keyword data type in the search index. For example, the column value in the data table is
"abc"
and the mapped column in the search index is of the Keyword type. If you set the query condition toMatchQuery("ab")
, no data is found because data of the Keyword data type cannot be tokenized. You cannot use match query to match the tokens.Case 2: The parameters are incorrectly configured in the query conditions. For example, the column value in the data table is
"abc"
and the mapped column in the search index is of the Keyword type. If you set the query condition toTermQuery("ab")
, no data is found.Case 3: If range query is used to query a Keyword column in the search index, the settings of the query condition are invalid. For example, the column value in the data table is 20 and the mapped column in the search index is of the Keyword type. If you set the query condition to
RangeQuery(>10)
, no data is found.NoteIn a range query, data of the Keyword data type is compared in alphabetical order and data of the Long and Double data types is compared based on the numeric values.
Case 4: The tokenization method is incorrectly specified. For example, the column value in the data table is
"abcdefg"
, the mapped column in the search index is of the Text type, and the tokenization method is set to single-word tokenization. If you set the query condition toMatchQuery("abcd")
, no data is found.
Solutions
Data in the data table is not correctly synchronized to the search index
Make sure that the data in the data table is synchronized to the search index. In most cases, the latency for incremental data synchronization is within 3 seconds. The latency for full data synchronization is directly proportional to the volume of data in the data table.
When you create a search index, make sure that the mappings of names and data types between the columns in the search index and the columns in the data table are correct. In addition, make sure that the data formats in the data table match the data types in the search index. For more information, see Data types, String types, Date data type, and Array and Nested data types.
NoteIf the configurations of the search index are invalid, you can create another search index or dynamically modify the schema of the current search index. For more information, see Create a search index and Dynamically modify the schema of a search index.
When you use the k-nearest neighbor (KNN) vector query feature, make sure that the attributes of the Vector field in the search index are the same as the attributes of the Vector field generated by the embedding system. The attributes of a Vector field include the number of dimensions, the data type, and the distance measurement algorithm. For more information, see KNN vector query.
An inappropriate query method is used
When you use a search index to query data, make sure that an appropriate query method is used and valid query conditions are specified. For more information, see Getting started.
Make sure that the correct tokenization method is specified. For more information about how to select the correct tokenization method, see Tokenization.