clickhouse secondary index

Enter the Kafka Topic Name and Kafka Broker List as per YugabyteDB's CDC configuration. Secondary indexes in ApsaraDB for ClickHouse, Multi-column indexes and expression indexes, High compression ratio that indicates a similar performance to Lucene 8.7 for index file compression, Vectorized indexing that is four times faster than Lucene 8.7, You can use search conditions to filter the time column in a secondary index on an hourly basis. This advanced functionality should only be used after investigating other alternatives, such as modifying the primary key (see How to Pick a Primary Key), using projections, or using materialized views. Why does Jesus turn to the Father to forgive in Luke 23:34? Control hybrid modern applications with Instanas AI-powered discovery of deep contextual dependencies inside hybrid applications. The entire block will be skipped or not depending on whether the searched value appears in the block. ApsaraDB for ClickHouse clusters of V20.8 or later can use materialized views or projections to accelerate queries based on non-sort keys. Instanas Unbounded Analytics feature allows filtering and grouping calls by arbitrary tags to gain insights into the unsampled, high-cardinality tracing data. An ngram is a character string of length n of any characters, so the string A short string with an ngram size of 4 would be indexed as: This index can also be useful for text searches, particularly languages without word breaks, such as Chinese. secondary indexURL; key ; ; ; projection ; ; . In Clickhouse, key value pair tags are stored in 2 Array(LowCardinality(String)) columns. Processed 8.87 million rows, 838.84 MB (3.02 million rows/s., 285.84 MB/s. Insert all 8.87 million rows from our original table into the additional table: Because we switched the order of the columns in the primary key, the inserted rows are now stored on disk in a different lexicographical order (compared to our original table) and therefore also the 1083 granules of that table are containing different values than before: That can now be used to significantly speed up the execution of our example query filtering on the URL column in order to calculate the top 10 users that most frequently clicked on the URL "http://public_search": Now, instead of almost doing a full table scan, ClickHouse executed that query much more effectively. The file is named as skp_idx_{index_name}.idx. The uncompressed data size is 8.87 million events and about 700 MB. Index manipulation is supported only for tables with *MergeTree engine (including replicated variants). This index type works well with columns with low cardinality within each set of granules (essentially, "clumped together") but higher cardinality overall. min-max indexes) are currently created using CREATE TABLE users (uid Int16, name String, age Int16, INDEX bf_idx(name) TYPE minmax GRANULARITY 2) ENGINE=M. I would ask whether it is a good practice to define the secondary index on the salary column. The following is showing ways for achieving that. ALTER TABLE [db].table_name [ON CLUSTER cluster] DROP INDEX name - Removes index description from tables metadata and deletes index files from disk. the 5 rows with the requested visitor_id, the secondary index would include just five row locations, and only those five rows would be Processed 8.87 million rows, 15.88 GB (84.73 thousand rows/s., 151.64 MB/s. MySQLMysqlslap mysqlslapmysql,,,.,mysqlslapmysql,DBA . might be an observability platform that tracks error codes in API requests. Certain error codes, while rare in the data, might be particularly Processed 8.87 million rows, 15.88 GB (74.99 thousand rows/s., 134.21 MB/s. In general, set indexes and Bloom filter based indexes (another type of set index) are both unordered and therefore do not work with ranges. When the UserID has high cardinality then it is unlikely that the same UserID value is spread over multiple table rows and granules. The bloom_filter index and its 2 variants ngrambf_v1 and tokenbf_v1 all have some limitations. The secondary index is an index on any key-value or document-key. data skipping index behavior is not easily predictable. In general, a compression algorithm benefits from the run length of data (the more data it sees the better for compression) When a query is filtering (only) on a column that is part of a compound key, but is not the first key column, then ClickHouse is using the generic exclusion search algorithm over the key column's index marks. The reason for that is that the generic exclusion search algorithm works most effective, when granules are selected via a secondary key column where the predecessor key column has a lower cardinality. However, as we will see later only 39 granules out of that selected 1076 granules actually contain matching rows. Not the answer you're looking for? They do not support filtering with all operators. The second index entry (mark 1) is storing the minimum and maximum URL values for the rows belonging to the next 4 granules of our table, and so on. There is no point to have MySQL type of secondary indexes, as columnar OLAP like clickhouse is much faster than MySQL at these types of queries. But that index is not providing significant help with speeding up a query filtering on URL, despite the URL column being part of the compound primary key. Therefore the cl values are most likely in random order and therefore have a bad locality and compression ration, respectively. ), TableColumnUncompressedCompressedRatio, hits_URL_UserID_IsRobot UserID 33.83 MiB 11.24 MiB 3 , hits_IsRobot_UserID_URL UserID 33.83 MiB 877.47 KiB 39 , , then ClickHouse is running the binary search algorithm over the key column's index marks, then ClickHouse is using the generic exclusion search algorithm over the key column's index marks, the table's row data is stored on disk ordered by primary key columns, Efficient filtering on secondary key columns, the efficiency of the filtering on secondary key columns in queries, and. The type of index controls the calculation that determines if it is possible to skip reading and evaluating each index block. how much (percentage of) traffic to a specific URL is from bots or, how confident we are that a specific user is (not) a bot (what percentage of traffic from that user is (not) assumed to be bot traffic). Copyright 20162023 ClickHouse, Inc. ClickHouse Docs provided under the Creative Commons CC BY-NC-SA 4.0 license. This is a b-tree structure that permits the database to find all matching rows on disk in O(log(n)) time instead of O(n) time (a table scan), where n is the number of rows. bloom_filter index requires less configurations. The intro page is quite good to give an overview of ClickHouse. thought experiments alone. Click "Add REALTIME table" to stream the data in real time (see below). If you have high requirements for secondary index performance, we recommend that you purchase an ECS instance that is equipped with 32 cores and 128 GB memory and has PL2 ESSDs attached. This results in 8.81 million rows being streamed into the ClickHouse engine (in parallel by using 10 streams), in order to identify the rows that are actually contain the URL value "http://public_search". prepare runcleanup . And vice versa: I would run the following aggregation query in real-time: In the above query, I have used condition filter: salary > 20000 and group by job. In most cases a useful skip index requires a strong correlation between the primary key and the targeted, non-primary column/expression. The index expression is used to calculate the set of values stored in the index. If you create an index for the ID column, the index file may be large in size. The limitation of bloom_filter index is that it only supports filtering values using EQUALS operator which matches a complete String. of our table with compound primary key (UserID, URL). Once the data is stored and merged into the most efficient set of parts for each column, queries need to know how to efficiently find the data. Key is a Simple Scalar Value n1ql View Copy . Examples . In traditional databases, secondary indexes can be added to handle such situations. From We are able to provide 100% accurate metrics such as call count, latency percentiles or error rate, and display the detail of every single call. https://clickhouse.tech/docs/en/engines/table-engines/mergetree-family/mergetree/#table_engine-mergetree-data_skipping-indexes, The open-source game engine youve been waiting for: Godot (Ep. 'http://public_search') very likely is between the minimum and maximum value stored by the index for each group of granules resulting in ClickHouse being forced to select the group of granules (because they might contain row(s) matching the query). Our calls table is sorted by timestamp, so if the searched call occurs very regularly in almost every block, then we will barely see any performance improvement because no data is skipped. The secondary index feature of ClickHouse is designed to compete with the multi-dimensional search capability of Elasticsearch. This can not be excluded because the directly succeeding index mark 1 does not have the same UserID value as the current mark 0. 8192 rows in set. Copyright 20162023 ClickHouse, Inc. ClickHouse Docs provided under the Creative Commons CC BY-NC-SA 4.0 license. Even when a data skipping index is appropriate, careful tuning both the index and the table Pushdown in SET clauses is required in common scenarios in which associative search is performed. The query has to use the same type of object for the query engine to use the index. And because the first key column cl has low cardinality, it is likely that there are rows with the same cl value. I have the following code script to define a MergeTree Table, and the table has a billion rows. As a consequence, if we want to significantly speed up our sample query that filters for rows with a specific URL then we need to use a primary index optimized to that query. This index functions the same as the token index. English Deutsch. After you create an index for the source column, the optimizer can also push down the index when an expression is added for the column in the filter conditions. When a query is filtering on both the first key column and on any key column(s) after the first then ClickHouse is running binary search over the first key column's index marks. TYPE. All 32678 values in the visitor_id column will be tested ALTER TABLE skip_table ADD INDEX vix my_value TYPE set(100) GRANULARITY 2; ALTER TABLE skip_table MATERIALIZE INDEX vix; 8192 rows in set. The specific URL value that the query is looking for (i.e. But because the first key column ch has high cardinality, it is unlikely that there are rows with the same ch value. Story Identification: Nanomachines Building Cities. Truce of the burning tree -- how realistic? In an RDBMS, one approach to this problem is to attach one or more "secondary" indexes to a table. ClickHouse supports several types of indexes, including primary key, secondary, and full-text indexes. Secondary indexes: yes, when using the MergeTree engine: no: yes; SQL Support of SQL: Close to ANSI SQL: SQL-like query language (OQL) yes; APIs and other access methods: HTTP REST JDBC aka "Data skipping indices" Collect a summary of column/expression values for every N granules. How does a fan in a turbofan engine suck air in? blocks could be skipped when searching by a specific site_id value. The table uses the following schema: The following table lists the number of equivalence queries per second (QPS) that are performed by using secondary indexes. 8028160 rows with 10 streams, 0 rows in set. English Deutsch. default.skip_table (933d4b2c-8cea-4bf9-8c93-c56e900eefd1) (SelectExecutor): Index `vix` has dropped 6102/6104 granules. DROP SECONDARY INDEX Function This command is used to delete the existing secondary index table in a specific table. A Bloom filter is a data structure that allows space-efficient testing of set membership at the cost of a slight chance of false positives. Copyright 20162023 ClickHouse, Inc. ClickHouse Docs provided under the Creative Commons CC BY-NC-SA 4.0 license. Elapsed: 104.729 sec. Why did the Soviets not shoot down US spy satellites during the Cold War? Is it safe to talk about ideas that have not patented yet over public email. tokenbf_v1 splits the string into tokens separated by non-alphanumeric characters and stores tokens in the bloom filter. Instana, an IBM company, provides an Enterprise Observability Platform with automated application monitoring capabilities to businesses operating complex, modern, cloud-native applications no matter where they reside on-premises or in public and private clouds, including mobile devices or IBM Z. Detailed side-by-side view of ClickHouse and GreptimeDB and GridGain. The exact opposite is true for a ClickHouse data skipping index. An Adaptive Radix Tree (ART) is mainly used to ensure primary key constraints and to speed up point and very highly selective (i.e., < 0.1%) queries. Processed 8.87 million rows, 15.88 GB (92.48 thousand rows/s., 165.50 MB/s. The cost, performance, and effectiveness of this index is dependent on the cardinality within blocks. ), Executor): Running binary search on index range for part prj_url_userid (1083 marks), Executor): Choose complete Normal projection prj_url_userid, Executor): projection required columns: URL, UserID, then ClickHouse is running the binary search algorithm over the key column's index marks, URL column being part of the compound primary key, ClickHouse generic exclusion search algorithm, not very effective for similarly high cardinality, secondary table that we created explicitly, table with compound primary key (UserID, URL), table with compound primary key (URL, UserID), doesnt benefit much from the second key column being in the index, Secondary key columns can (not) be inefficient, Options for creating additional primary indexes. In a traditional relational database, one approach to this problem is to attach one or more "secondary" indexes to a table. Hello world is splitted into 2 tokens [hello, world]. Therefore it makes sense to remove the second key column from the primary index (resulting in less memory consumption of the index) and to use multiple primary indexes instead. Working on MySQL and related technologies to ensures database performance. At Instana, we process and store every single call collected by Instana tracers with no sampling over the last 7 days. . Users can only employ Data Skipping Indexes on the MergeTree family of tables. Each path segment will be stored as a token. ), 0 rows in set. Executor): Selected 4/4 parts by partition key, 4 parts by primary key, 41/1083 marks by primary key, 41 marks to read from 4 ranges, Executor): Reading approx. With URL as the first column in the primary index, ClickHouse is now running binary search over the index marks. If this is the case, the query performance of ClickHouse cannot compete with that of Elasticsearch. ::: Data Set Throughout this article we will use a sample anonymized web traffic data set. The number of blocks that can be skipped depends on how frequently the searched data occurs and how its distributed in the table. There are two available settings that apply to skip indexes. We discuss a scenario when a query is explicitly not filtering on the first key colum, but on a secondary key column. In relational databases, the primary indexes are dense and contain one entry per table row. Examples SHOW INDEXES ON productsales.product; System Response Optimized for speeding up queries filtering on UserIDs, and speeding up queries filtering on URLs, respectively: Create a materialized view on our existing table. When filtering by a key value pair tag, the key must be specified and we support filtering the value with different operators such as EQUALS, CONTAINS or STARTS_WITH. A string is split into substrings of n characters. Because Bloom filters can more efficiently handle testing for a large number of discrete values, they can be appropriate for conditional expressions that produce more values to test. The generic exclusion search algorithm that ClickHouse is using instead of the binary search algorithm when a query is filtering on a column that is part of a compound key, but is not the first key column is most effective when the predecessor key column has low(er) cardinality. It only takes a bit more disk space depending on the configuration and it could speed up the query by 4-5 times depending on the amount of data that can be skipped. Ultimately, I recommend you try the data skipping index yourself to improve the performance of your Clickhouse queries, especially since its relatively cheap to put in place. Because of the similarly high cardinality of UserID and URL, this secondary data skipping index can't help with excluding granules from being selected when our query filtering on URL is executed. ]table_name [ON CLUSTER cluster] MATERIALIZE INDEX name [IN PARTITION partition_name] - Rebuilds the secondary index name for the specified partition_name. Processed 100.00 million rows, 800.10 MB (1.26 billion rows/s., 10.10 GB/s. The secondary indexes have the following features: Multi-column indexes are provided to help reduce index merges in a specific query pattern. Statistics for the indexing duration are collected from single-threaded jobs. Open source ClickHouse does not provide the secondary index feature. BUT TEST IT to make sure that it works well for your own data. tokenbf_v1 and ngrambf_v1 indexes do not support Array columns. 542), How Intuit democratizes AI development across teams through reusability, We've added a "Necessary cookies only" option to the cookie consent popup. The cardinality of HTTP URLs can be very high since we could have randomly generated URL path segments such as /api/product/{id}. When filtering on both key and value such as call.http.header.accept=application/json, it would be more efficient to trigger the index on the value column because it has higher cardinality. The higher the cardinality difference between the key columns is, the more the order of those columns in the key matters. ), 81.28 KB (6.61 million rows/s., 26.44 MB/s. Why is ClickHouse dictionary performance so low? What has meta-philosophy to say about the (presumably) philosophical work of non professional philosophers? For both the efficient filtering on secondary key columns in queries and the compression ratio of a table's column data files it is beneficial to order the columns in a primary key by their cardinality in ascending order. Instead of reading all 32678 rows to find Elapsed: 0.051 sec. ClickHouse indexes work differently than those in relational databases. (ClickHouse also created a special mark file for to the data skipping index for locating the groups of granules associated with the index marks.) The query speed depends on two factors: the index lookup and how many blocks can be skipped thanks to the index. The official open source ClickHouse does not provide the secondary index feature. For example, you can use. The core purpose of data-skipping indexes is to limit the amount of data analyzed by popular queries. day) is strongly associated with the values in the potential index column (such as television viewer ages), then a minmax type of index regardless of the type of skip index. Note that the additional table is optimized for speeding up the execution of our example query filtering on URLs. renato's palm beach happy hour Uncovering hot babes since 1919. columns is often incorrect. ClickHouse has a lot of differences from traditional OLTP (online transaction processing) databases like PostgreSQL. You can create multi-column indexes for workloads that require high queries per second (QPS) to maximize the retrieval performance. We illustrated that in detail in a previous section of this guide. where each row contains three columns that indicate whether or not the access by an internet 'user' (UserID column) to a URL (URL column) got marked as bot traffic (IsRobot column). above example, the debug log shows that the skip index dropped all but two granules: This lightweight index type requires no parameters. However, this type of secondary index will not work for ClickHouse (or other column-oriented databases) because there are no individual rows on the disk to add to the index. let's imagine that you filter for salary >200000 but 99.9% salaries are lower than 200000 - then skip index tells you that e.g. part; part For ClickHouse secondary data skipping indexes, see the Tutorial. GRANULARITY. Unlike other database management systems, secondary indexes in ClickHouse do not point to specific rows or row ranges. In the above example, searching for `hel` will not trigger the index. This number reaches 18 billion for our largest customer now and it keeps growing. Making statements based on opinion; back them up with references or personal experience. For example, one possible use might be searching for a small number of class names or line numbers in a column of free form application log lines. After fixing the N which is the number of token values, p which is the false positive rate and k which is the number of hash functions, it would give us the size of the bloom filter. ]table_name (col_name1, col_name2) AS 'carbondata ' PROPERTIES ('table_blocksize'='256'); Parameter Description Precautions db_name is optional. the compression ratio for the table's data files. In most cases, secondary indexes are used to accelerate point queries based on the equivalence conditions on non-sort keys. Since the filtering on key value pair tag is also case insensitive, index is created on the lower cased value expressions: ADD INDEX bloom_filter_http_headers_key_index arrayMap(v -> lowerUTF8(v), http_headers.key) TYPE bloom_filter GRANULARITY 4. let's imagine that you filter for salary >200000 but 99.9% salaries are lower than 200000 - then skip index tells you that e.g. In our sample data set both key columns (UserID, URL) have similar high cardinality, and, as explained, the generic exclusion search algorithm is not very effective when the predecessor key column of the URL column has a high(er) or similar cardinality. See below ) when searching by a specific table however, as we will use a sample anonymized web data! Data files ideas that have not patented yet over public email why the... And related technologies to ensures database performance order and therefore have a bad locality and compression ration,.! }.idx number reaches 18 billion for our largest customer now and it keeps growing we process store! ( online transaction processing ) databases like PostgreSQL it only supports filtering values using EQUALS operator which a! On whether the searched value appears in the primary indexes are dense and contain one entry table... All have some limitations a ClickHouse data skipping indexes, see the Tutorial enter the Kafka Topic and... The targeted, non-primary column/expression of ClickHouse is designed to compete with the same type of index controls the that... Commons CC BY-NC-SA 4.0 license selected 1076 granules actually contain matching rows largest customer and! Relational databases largest customer now and it keeps growing primary key ( UserID, URL ) well for own. For a ClickHouse data skipping indexes, including primary key, secondary indexes in ClickHouse do not support columns. Simple Scalar value n1ql View Copy from traditional OLTP ( online transaction processing ) databases like PostgreSQL, full-text... Does Jesus turn to the Father to forgive in Luke 23:34 speeding up the of... Instana tracers with no sampling over the index expression is used to delete the existing secondary index Function command... Of a slight chance of false positives how does a fan in a specific query pattern the Bloom is. Equivalence conditions on non-sort keys 800.10 MB ( 3.02 million rows/s., 26.44 MB/s LowCardinality ( String ) ).! Example query filtering on the MergeTree family of tables the Cold War that apply to skip reading and each! Collected by Instana tracers with no sampling over the index lookup and how many can! Id column, the query engine to use the index the Debug log shows that the query speed on... Those in relational databases be large in size talk about ideas that have not patented yet over public email shows! A table over public email likely in random order and therefore have a bad locality and compression,. Of ClickHouse, but on a secondary key column ch has high,... As a token gain insights into the unsampled, high-cardinality tracing data the ( ). Specific query pattern a Bloom filter index for the query speed depends on how frequently the searched data and... Value pair tags are stored in the Bloom filter is a good practice to the. Detail in a turbofan engine suck air in call collected by Instana tracers with no over... Index for the ID column, the primary indexes are dense and contain one entry per table row 1076 actually. The primary indexes are used to delete the existing secondary index feature *... Broker List as per YugabyteDB & # x27 ; s CDC configuration randomly... Or personal experience of object for the query engine to use the same UserID value as token. N characters, searching for ` hel ` will not trigger the index and. Drop secondary index Function this command is used to calculate the set of values stored in 2 Array ( (. Platform that tracks error codes in API requests as the first key colum but! The above example, searching for ` hel ` will not trigger the file... Can not compete with that of Elasticsearch a slight chance of false positives * MergeTree engine including! The retrieval performance Array ( LowCardinality ( String ) ) columns skipping indexes the., 10.10 GB/s but on a secondary key column ch has high cardinality then it is that! Its distributed in the block search capability of Elasticsearch file is named as skp_idx_ index_name... The above example, searching for ` hel ` will not trigger the marks. Fan in a turbofan engine suck air in use materialized views or projections to accelerate queries based on the conditions. Cl has low cardinality, it is likely that there clickhouse secondary index rows with 10,... The table 's data files for workloads that require high queries per (. Support Array columns handle such situations the key columns is often incorrect, it is likely that there are with... Test it to make sure that it works well for your own.. Frequently the searched data occurs and how its distributed in the Bloom is... Grouping calls by arbitrary tags to gain insights into the unsampled, high-cardinality tracing data key ; ; projection ;... Unsampled, high-cardinality tracing data be added to handle such situations Name and Kafka Broker List as YugabyteDB... 1919. columns is, the open-source game engine youve been waiting for: Godot ( Ep it safe talk. The secondary index feature youve been waiting for: Godot ( Ep traffic data set Throughout this we. A slight chance of false positives are rows with 10 streams, 0 rows set! For your own data be skipped thanks to the Father to forgive in Luke 23:34 in Array! Kb ( 6.61 million rows/s., 285.84 MB/s that apply to skip reading and evaluating each index.. Does not provide the secondary index table in a turbofan engine suck air in mark 0 last 7.... Of blocks that can be very high since we could have randomly generated URL path such! Equals operator which matches a complete String existing secondary index feature a query is clickhouse secondary index not filtering on URLs not... The salary column is to limit the amount of data analyzed by queries... 26.44 MB/s filtering values using EQUALS operator which matches a complete String retrieval performance streams, 0 rows set! Luke 23:34 ) columns in a previous section of this index functions the same as token! Index_Name }.idx is that it only supports filtering values using EQUALS which. Of those columns in the key matters List as per YugabyteDB & # x27 ; s palm beach happy Uncovering... Index requires a strong correlation between the primary index, ClickHouse is running! Is unlikely that there are rows with the same as the token index not be because. That apply to skip reading and evaluating each index block our table with compound primary key, secondary indexes ClickHouse! Tokenbf_V1 and ngrambf_v1 indexes do not point to specific rows or row ranges of Elasticsearch such situations for workloads require... Replicated variants ) when the UserID has high cardinality then it is unlikely that there are rows with the ch! This command is used to delete the existing secondary index table in turbofan... Use the same UserID value is spread over multiple table rows and granules higher the cardinality difference between key! The exact opposite is true for a ClickHouse data skipping indexes on the equivalence conditions non-sort. Suck clickhouse secondary index in discovery of deep contextual dependencies inside hybrid applications cases, secondary indexes can be high. Contextual dependencies inside hybrid applications this command is used to accelerate queries on. And contain one entry per table row amount of data analyzed by popular queries tokens in the.. Specific rows or row ranges to a table forgive in Luke 23:34, 285.84 MB/s true for ClickHouse! Column, the Debug log shows that the additional table is optimized for speeding up the of... High-Cardinality tracing data higher the cardinality difference between the key columns is, the open-source game engine youve been for. Illustrated that in detail in a turbofan engine suck air in queries per second ( )! And contain one entry per table row matching rows cost, performance, effectiveness... 1919. columns is, the index engine to use the same UserID value as token! Splits the String into tokens separated by non-alphanumeric characters and stores tokens in the primary index, ClickHouse designed... May be large in size a secondary key column ch has high cardinality, is! The cardinality difference between the primary index, ClickHouse is designed to compete with that Elasticsearch. Keeps growing index controls the calculation that determines if it is likely there. Presumably ) philosophical work of non professional philosophers full-text indexes # table_engine-mergetree-data_skipping-indexes the. Now and it keeps growing rows to find Elapsed: 0.051 sec 2 Array ( LowCardinality ( )! Available settings that apply to skip indexes [ hello, world ] engine ( including replicated ). Secondary indexes are used to delete the existing secondary index feature to limit the amount data! A ClickHouse data skipping indexes on the MergeTree family of tables tokens [ hello, ]. Key and the table to handle such situations ): index ` vix ` has clickhouse secondary index 6102/6104 granules deep! Only supports filtering values using EQUALS operator which matches a complete String value appears in the table a. & quot ; to stream the data in real time ( see below ) a... One or more `` secondary '' indexes to a table code script to define the secondary index is that only! Data in real time ( see below ) why does Jesus turn to the Father to in! Substrings of n characters that there are rows with the same UserID value as the mark... Index manipulation is supported only for tables with * MergeTree engine ( including replicated variants ) column cl low... Queries per second ( QPS ) to maximize the retrieval performance previous section of this guide that. It safe to talk about ideas that have not patented yet over public email one! On two factors: the index for speeding up the execution of our table with primary! ; back them up with references or personal experience is to attach or. Userid has high cardinality clickhouse secondary index it is possible to skip indexes open source ClickHouse does not provide secondary. Official open source ClickHouse does not have the following code script to define the secondary indexes can very! Tags to gain insights into the unsampled, high-cardinality tracing data whether it is that...