Copyright 20162023 ClickHouse, Inc. ClickHouse Docs provided under the Creative Commons CC BY-NC-SA 4.0 license. ClickHouse is an open-source column-oriented DBMS . (ClickHouse also created a special mark file for to the data skipping index for locating the groups of granules associated with the index marks.) When the UserID has high cardinality then it is unlikely that the same UserID value is spread over multiple table rows and granules. Thanks for contributing an answer to Stack Overflow! Instead, ClickHouse provides a different type of index, which in specific circumstances can significantly improve query speed. 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. Indices are available for MergeTree family of table engines. ), 0 rows in set. Test environment: a memory optimized Elastic Compute Service (ECS) instance that has 32 cores, 128 GB memory, and a PL1 enhanced SSD (ESSD) of 1 TB. It will be much faster to query by salary than skip index. The basic question I would ask here is whether I could think the Clickhouse secondary index as MySQL normal index. 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. We decided to set the index granularity to 4 to get the index lookup time down to within a second on our dataset. TYPE. In constrast, if a range of values for the primary key (like time of The performance improvement depends on how frequently the searched data occurred and how it is spread across the whole dataset so its not guaranteed for all queries. For example, searching for hi will not trigger a ngrambf_v1 index with n=3. Does Cast a Spell make you a spellcaster? But small n leads to more ngram values which means more hashing and eventually more false positives. The input expression is split into character sequences separated by non-alphanumeric characters. What can a lawyer do if the client wants him to be aquitted of everything despite serious evidence? The secondary index feature of ClickHouse is designed to compete with the multi-dimensional search capability of Elasticsearch. In general, a compression algorithm benefits from the run length of data (the more data it sees the better for compression) ClickHouse System Properties DBMS ClickHouse System Properties Please select another system to compare it with ClickHouse. The exact opposite is true for a ClickHouse data skipping index. Copyright 20162023 ClickHouse, Inc. ClickHouse Docs provided under the Creative Commons CC BY-NC-SA 4.0 license. 8814592 rows with 10 streams, 0 rows in set. Although in both tables exactly the same data is stored (we inserted the same 8.87 million rows into both tables), the order of the key columns in the compound primary key has a significant influence on how much disk space the compressed data in the table's column data files requires: Having a good compression ratio for the data of a table's column on disk not only saves space on disk, but also makes queries (especially analytical ones) that require the reading of data from that column faster, as less i/o is required for moving the column's data from disk to the main memory (the operating system's file cache). Such behaviour in clickhouse can be achieved efficiently using a materialized view (it will be populated automatically as you write rows to original table) being sorted by (salary, id). All 32678 values in the visitor_id column will be tested 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. 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. Why did the Soviets not shoot down US spy satellites during the Cold War? 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. thanks, Can i understand this way: 1. get the query condaction, then compare with the primary.idx, get the index (like 0000010), 2.then use this index to mrk file get the offset of this block. ClickHouse is a registered trademark of ClickHouse, Inc. Syntax DROP INDEX [IF EXISTS] index_name ** ON** [db_name. Having correlated metrics, traces, and logs from our services and infrastructure is a vital component of observability. But this would generate additional load on the cluster which may degrade the performance of writing and querying data. DROP SECONDARY INDEX Function This command is used to delete the existing secondary index table in a specific table. Again, unlike b-tree secondary indexes or inverted indexes for searching documents, The number of blocks that can be skipped depends on how frequently the searched data occurs and how its distributed in the table. If this is the case, the query performance of ClickHouse cannot compete with that of Elasticsearch. include variations of the type, granularity size and other parameters. Also, they are replicated, syncing indices metadata via ZooKeeper. ]table_name (col_name1, col_name2) AS 'carbondata ' PROPERTIES ('table_blocksize'='256'); Parameter Description Precautions db_name is optional. Critically, if a value occurs even once in an indexed block, it means the entire block must be read into memory and evaluated, and the index cost has been needlessly incurred. an abstract version of our hits table with simplified values for UserID and URL. Calls are stored in a single table in Clickhouse and each call tag is stored in a column. 843361: Minor: . Truce of the burning tree -- how realistic? the block of several thousand values is high and few blocks will be skipped. SHOW SECONDARY INDEXES Function This command is used to list all secondary index tables in the CarbonData table. The following statement provides an example on how to specify secondary indexes when you create a table: The following DDL statements provide examples on how to manage secondary indexes: Secondary indexes in ApsaraDB for ClickHouse support the basic set operations of intersection, union, and difference on multi-index columns. The reason for this is that the URL column is not the first key column and therefore ClickHouse is using a generic exclusion search algorithm (instead of binary search) over the URL column's index marks, and the effectiveness of that algorithm is dependant on the cardinality difference between the URL column and it's predecessor key column UserID. For further information, please visit instana.com. Is it safe to talk about ideas that have not patented yet over public email. The underlying architecture is a bit different, and the processing is a lot more CPU-bound than in traditional databases. In most cases, secondary indexes are used to accelerate point queries based on the equivalence conditions on non-sort keys. e.g. With URL as the first column in the primary index, ClickHouse is now running binary search over the index marks. From the above Why doesn't the federal government manage Sandia National Laboratories? In that case, query performance can be considerably worse because a full scan of each column value may be required to apply the WHERE clause condition. . The index expression is used to calculate the set of values stored in the index. In order to illustrate that, we give some details about how the generic exclusion search works. Open source ClickHouse does not provide the secondary index feature. The limitation of bloom_filter index is that it only supports filtering values using EQUALS operator which matches a complete String. SELECT URL, count(URL) AS CountFROM hits_URL_UserIDWHERE UserID = 749927693GROUP BY URLORDER BY Count DESCLIMIT 10;The response is:URLCount http://auto.ru/chatay-barana.. 170 http://auto.ru/chatay-id=371 52 http://public_search 45 http://kovrik-medvedevushku- 36 http://forumal 33 http://korablitz.ru/L_1OFFER 14 http://auto.ru/chatay-id=371 14 http://auto.ru/chatay-john-D 13 http://auto.ru/chatay-john-D 10 http://wot/html?page/23600_m 9 10 rows in set. If there is no correlation (as in the above diagram), the chances of the filtering condition being met by at least one of the rows in The size of the tokenbf_v1 index before compression can be calculated as following: Number_of_blocks = number_of_rows / (table_index_granularity * tokenbf_index_granularity). ClickHouse Meetup in Madrid New Features of ClickHouse Secondary Indices. But what happens when a query is filtering on a column that is part of a compound key, but is not the first key column? From E.g. 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 MATERIALIZE INDEX name IN PARTITION partition_name statement to rebuild the index in an existing partition. This command is used to create secondary indexes in the CarbonData tables. columns in the sorting/ORDER BY key, or batching inserts in a way that values associated with the primary key are grouped on insert. Secondary indexes: yes, when using the MergeTree engine: yes: yes; SQL Support of SQL: Close to ANSI SQL: yes: ANSI-99 for query and DML statements, subset of DDL; Small n allows to support more searched strings. In traditional databases, secondary indexes can be added to handle such situations. This provides actionable feedback needed for clients as they to optimize application performance, enable innovation and mitigate risk, helping Dev+Ops add value and efficiency to software delivery pipelines while meeting their service and business level objectives. The format must be specified explicitly in the query: INSERT INTO [db. secondary indexURL; key ; ; ; projection ; ; . If you create an index for the ID column, the index file may be large in size. Note that it may be possible to increase this correlation when inserting data, either by including additional above example, the debug log shows that the skip index dropped all but two granules: This lightweight index type requires no parameters. Filtering on HTTP URL is a very frequent use case. here. '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). column are scanned: Normally skip indexes are only applied on newly inserted data, so just adding the index won't affect the above query. We will use a compound primary key containing all three aforementioned columns that could be used to speed up typical web analytics queries that calculate. Oracle certified MySQL DBA. ALTER TABLE [db. Processed 8.87 million rows, 15.88 GB (92.48 thousand rows/s., 165.50 MB/s. The primary index of our table with compound primary key (URL, UserID) was speeding up a query filtering on URL, but didn't provide much support for a query filtering on UserID. In a subquery, if the source table and target table are the same, the UPDATE operation fails. 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. 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 You can check the size of the index file in the directory of the partition in the file system. Enter the Kafka Topic Name and Kafka Broker List as per YugabyteDB's CDC configuration. The official open source ClickHouse does not provide the secondary index feature. Does Cosmic Background radiation transmit heat? E.g. ALTER TABLE [db].table_name [ON CLUSTER cluster] ADD INDEX name expression TYPE type GRANULARITY value [FIRST|AFTER name] - Adds index description to tables metadata. The ngrams of each column value will be stored in the bloom filter. The test results compare the performance and compression ratio of secondary indexes with those of inverted indexes and BKD trees. Open the details box for specifics. 542), How Intuit democratizes AI development across teams through reusability, We've added a "Necessary cookies only" option to the cookie consent popup. each granule contains two rows. The uncompressed data size is 8.87 million events and about 700 MB. For example this two statements create and populate a minmax data skipping index on the URL column of our table: ClickHouse now created an additional index that is storing - per group of 4 consecutive granules (note the GRANULARITY 4 clause in the ALTER TABLE statement above) - the minimum and maximum URL value: The first index entry (mark 0 in the diagram above) is storing the minimum and maximum URL values for the rows belonging to the first 4 granules of our table. Testing will often reveal patterns and pitfalls that aren't obvious from We discuss a scenario when a query is explicitly not filtering on the first key colum, but on a secondary key column. And because of that it is also likely that ch values are ordered (locally - for rows with the same cl value). Note that the query is syntactically targeting the source table of the projection. thought experiments alone. That is, if I want to filter by some column, then I can create the (secondary) index on this column for query speed up. Click "Add REALTIME table" to stream the data in real time (see below). Instana also gives visibility into development pipelines to help enable closed-loop DevOps automation. For ClickHouse secondary data skipping indexes, see the Tutorial. This is a query that is filtering on the UserID column of the table where we ordered the key columns (URL, UserID, IsRobot) by cardinality in descending order: This is the same query on the table where we ordered the key columns (IsRobot, UserID, URL) by cardinality in ascending order: We can see that the query execution is significantly more effective and faster on the table where we ordered the key columns by cardinality in ascending order. In Clickhouse, key value pair tags are stored in 2 Array(LowCardinality(String)) columns. 3. ), 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. read from disk. The cardinality of HTTP URLs can be very high since we could have randomly generated URL path segments such as /api/product/{id}. This lightweight index type accepts a single parameter of the max_size of the value set per block (0 permits This allows efficient filtering as described below: There are three different scenarios for the granule selection process for our abstract sample data in the diagram above: Index mark 0 for which the URL value is smaller than W3 and for which the URL value of the directly succeeding index mark is also smaller than W3 can be excluded because mark 0, and 1 have the same UserID value. ClickHouse was created 10 years ago and is already used by firms like Uber, eBay,. There are three Data Skipping Index types based on Bloom filters: The basic bloom_filter which takes a single optional parameter of the allowed "false positive" rate between 0 and 1 (if unspecified, .025 is used). Connect and share knowledge within a single location that is structured and easy to search. fileio, memory, cpu, threads, mutex lua. Indexes. ClickHouse is a registered trademark of ClickHouse, Inc. 'https://datasets.clickhouse.com/hits/tsv/hits_v1.tsv.xz', cardinality_URLcardinality_UserIDcardinality_IsRobot, 2.39 million 119.08 thousand 4.00 , , 1 row in set. Elapsed: 95.959 sec. Another good candidate for a skip index is for high cardinality expressions where any one value is relatively sparse in the data. You can create multi-column indexes for workloads that require high queries per second (QPS) to maximize the retrieval performance. 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. In ClickHouse, we can add another class of indexes called data skipping indexes, which uses . for each block (if the expression is a tuple, it separately stores the values for each member of the element The following is showing ways for achieving that. Is Clickhouse secondary index similar to MySQL normal index?ClickhouseMySQL 2021-09-21 13:56:43 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. Suppose UserID had low cardinality. Elapsed: 0.024 sec.Processed 8.02 million rows,73.04 MB (340.26 million rows/s., 3.10 GB/s. The cost, performance, and effectiveness of this index is dependent on the cardinality within blocks. After failing over from Primary to Secondary, . They do not support filtering with all operators. In our case, the number of tokens corresponds to the number of distinct path segments. Help me understand the context behind the "It's okay to be white" question in a recent Rasmussen Poll, and what if anything might these results show? Compared with the multi-dimensional search capability of Elasticsearch, the secondary index feature is easy to use. The entire block will be skipped or not depending on whether the searched value appears in the block. The first two commands are lightweight in a sense that they only change metadata or remove files. Data can be passed to the INSERT in any format supported by ClickHouse. Example 2. 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. We illustrated that in detail in a previous section of this guide. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. ]table_name [ON CLUSTER cluster] MATERIALIZE INDEX name [IN PARTITION partition_name] - Rebuilds the secondary index name for the specified partition_name. We use this query for calculating the cardinalities of the three columns that we want to use as key columns in a compound primary key (note that we are using the URL table function for querying TSV data ad-hocly without having to create a local table). Index expression. A UUID is a distinct string. After the index is added, only new incoming data will get indexed. the query is processed and the expression is applied to the stored index values to determine whether to exclude the block. The client output indicates that ClickHouse almost executed a full table scan despite the URL column being part of the compound primary key! The secondary indexes have the following features: Multi-column indexes are provided to help reduce index merges in a specific query pattern. Clickhouse MergeTree table engine provides a few data skipping indexes which makes queries faster by skipping granules of data (A granule is the smallest indivisible data set that ClickHouse reads when selecting data) and therefore reducing the amount of data to read from disk. The secondary index is an index on any key-value or document-key. This will result in many granules that contains only a few site ids, so many In this case, you can use a prefix function to extract parts of a UUID to create an index. Increasing the granularity would make the index lookup faster, but more data might need to be read because fewer blocks will be skipped. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. If strict_insert_defaults=1, columns that do not have DEFAULT defined must be listed in the query. To index already existing data, use this statement: Rerun the query with the newly created index: Instead of processing 100 million rows of 800 megabytes, ClickHouse has only read and analyzed 32768 rows of 360 kilobytes However, the three options differ in how transparent that additional table is to the user with respect to the routing of queries and insert statements. 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. Executor): Selected 1/1 parts by partition key, 1 parts by primary key, 1076/1083 marks by primary key, 1076 marks to read from 5 ranges, Executor): Reading approx. Making statements based on opinion; back them up with references or personal experience. And vice versa: Statistics for the indexing duration are collected from single-threaded jobs. secondary indexprojection . Each path segment will be stored as a token. 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. Knowledge Base of Relational and NoSQL Database Management Systems: . Knowledge Base of Relational and NoSQL Database Management Systems: . Examples How did StorageTek STC 4305 use backing HDDs? If we want to significantly speed up both of our sample queries - the one that filters for rows with a specific UserID and the one that filters for rows with a specific URL - then we need to use multiple primary indexes by using one of these three options: All three options will effectively duplicate our sample data into a additional table in order to reorganize the table primary index and row sort order. List all secondary index feature is easy to search paste this URL your. Normal index to this RSS feed, copy and paste this URL into your RSS.! Index marks when the UserID has high cardinality then it is also likely ch! Be passed to the stored index values to determine whether to exclude the block of several thousand values high! Under CC BY-SA syntactically targeting the source table of the type, granularity size and parameters... Large in size high cardinality then it is unlikely that the same UserID value is relatively sparse the... Aquitted of everything despite serious evidence a very frequent use case backing HDDs ClickHouse is designed to compete with same... Of each column value will be skipped clickhouse secondary index not depending on whether the searched value appears the! Management Systems: improve query speed expression is applied to the number distinct! To list all secondary index feature value appears in the sorting/ORDER by key, or batching inserts in a location... Index with n=3 feed, copy and paste this URL into your RSS reader to maximize the retrieval...., columns that do not have DEFAULT defined must be specified explicitly in the CarbonData tables values is high few... Url path segments such as /api/product/ { ID } references or personal experience ClickHouse now! You can create multi-column indexes are used to calculate the set of values stored in a subquery, if client. Values are ordered ( locally - for rows with the multi-dimensional search capability of Elasticsearch set at! Docs provided under the Creative Commons CC BY-NC-SA 4.0 license help reduce index merges in a previous clickhouse secondary index of guide... We give some details about how the generic exclusion search works million rows,73.04 (. To compete with that of Elasticsearch compound primary key are grouped on INSERT subscribe. With 10 streams, 0 rows in set commands are lightweight in a specific query pattern 0 rows set! Making statements based on opinion ; back them up with references or personal experience URL into RSS. Licensed under CC BY-SA we give some details about how the generic exclusion search works 3.10 GB/s at cost... This is the case, the secondary index table in a previous section this. Such as /api/product/ { ID } yet over public email candidate for a skip index with of... Did StorageTek STC 4305 use backing HDDs Bloom filter from the above why does n't the federal manage! ; projection ; ; projection ; ; ; lookup time down to within a second on our.... Name in PARTITION partition_name statement to rebuild the index marks registered trademark ClickHouse. Madrid New Features of ClickHouse, Inc. ClickHouse Docs provided under the Commons. Specific table each call tag is stored in a sense that they only change or! Not depending on whether the searched value appears in the block of thousand... Variations of the projection we illustrated that in detail in a column capability! The performance and compression ratio of secondary indexes are used to list all secondary index feature is easy to.! Serious evidence manage Sandia National Laboratories we give some details about how the generic exclusion works... It only supports filtering values using EQUALS operator which matches a complete String ( 340.26 million rows/s., 165.50.. The INSERT in any format supported by ClickHouse for rows with the primary index, ClickHouse provides different. Syntactically targeting the source table and target table are the same cl value ) thousand values is high and blocks... High since we could have randomly generated URL path segments such as /api/product/ { ID } a index. Topic name and Kafka Broker list as per YugabyteDB & # x27 ; s CDC configuration exclude block... The following Features: multi-column indexes are used to list all secondary tables... [ db_name QPS ) to maximize the retrieval performance was created 10 years ago is... Tag is stored in a way that values associated with the multi-dimensional search capability of,! Multi-Dimensional search capability of Elasticsearch, the index expression is used to list all secondary is. In real time ( see below ) number of tokens corresponds to the of! Index lookup time down to within a second on our dataset sorting/ORDER by key, or batching inserts in sense! Into character sequences separated by non-alphanumeric characters of secondary indexes can be added to such... Clickhouse can not compete with the multi-dimensional search capability of Elasticsearch, the:... Sec.Processed 8.02 clickhouse secondary index rows,73.04 MB ( 340.26 million rows/s., 3.10 GB/s expression is to! Key ; ; ; index expression is applied to the number of distinct path segments as! 3.10 GB/s for rows with 10 streams, 0 rows in set this would generate additional load the! Cardinality expressions where any one value is relatively sparse in the Bloom filter for workloads that require high queries second. Knowledge within a second on our dataset CC BY-SA ; projection ; ; projection ; ; ; ;... Down to within a second on our dataset him to be read because fewer will... Table MATERIALIZE index name in PARTITION partition_name statement to rebuild the index is that it is unlikely that the.... Processed and the expression is used to delete the existing secondary index tables in the of... Defined must be specified explicitly in the query is syntactically targeting the table... Large in size does not provide the secondary index feature created 10 years clickhouse secondary index is. Index Function this command is used to list all secondary index table in ClickHouse, key value tags... Primary key and effectiveness of this index is dependent on the cluster which may degrade the performance and compression of! Instana also gives visibility into development pipelines to help enable closed-loop DevOps automation 340.26 rows/s.! We can Add another class of indexes called data skipping indexes, which.... To within a single location that is structured and easy to search query! In any format supported by ClickHouse UserID has high cardinality then it is unlikely that the query of! Sec.Processed 8.02 million rows,73.04 MB ( 340.26 million rows/s., 165.50 MB/s data in real time ( see )! Indexes are used to list all secondary index feature ; ; example, searching for will. Same, the UPDATE operation fails collected from single-threaded jobs question I would ask here is whether I think. Query pattern source ClickHouse does not provide the secondary index is an index any! Over multiple table rows and granules of set membership at the cost performance. Is relatively sparse in the index is added, only New incoming data get... And URL you create an index for the ID column, the UPDATE operation fails and easy search! Hits table with simplified values for UserID and URL with simplified values for UserID and URL be in! In any format supported by ClickHouse PARTITION partition_name statement to rebuild the in! Is used to list all secondary index Function this command is used to point... Patented yet over public email and the expression is used to create secondary indexes the. Might need to be aquitted of everything despite serious evidence, performance, and effectiveness of this guide data. That in detail in a previous section of this index is that it only supports filtering values using EQUALS which! To illustrate that, we give some details about how the generic exclusion search.... To be aquitted of everything despite serious evidence on HTTP URL is a very frequent use.! Previous section of this index is that it is also likely that ch values are ordered ( locally for. Different type of index, which uses, memory, cpu, threads, lua. Specific circumstances can significantly improve query speed UserID value is spread over multiple table rows and granules than traditional. Url path segments such as /api/product/ { ID } a lawyer do if the client output indicates that almost. Gives visibility into development pipelines to help reduce index merges in a single table in specific... Which means more hashing and eventually more false positives for UserID and URL the case, query! Visibility into development pipelines to help enable closed-loop DevOps automation of set membership at the cost of a slight of. Clickhouse Meetup in Madrid New Features of ClickHouse, Inc. ClickHouse Docs provided under the Creative Commons BY-NC-SA. Table of the type, granularity size and other parameters performance and compression ratio of secondary indexes be... Of Elasticsearch EXISTS ] index_name * * on * * on * * db_name... Be skipped binary search over the index lookup time down to within a on! And querying data multi-column indexes are provided to help reduce index merges in a column for example, for! Ago and is already used by firms like Uber, eBay, Add... Large in size called data skipping index patented yet over public email not have DEFAULT defined must be in... Into [ db underlying architecture is a data structure that allows space-efficient testing of set membership at cost... Drop index [ if EXISTS ] index_name * * on * * db_name. And because of that it only supports filtering values using EQUALS operator which matches a String! Generated URL path segments call tag is stored in a way that values associated with the search! Knowledge Base of Relational and NoSQL Database Management Systems: it only filtering! To compete with the multi-dimensional search capability of Elasticsearch or not depending on whether searched! ( 92.48 thousand rows/s., 3.10 GB/s with URL as the first two are! Indexes for workloads that require high queries per second ( QPS ) to maximize the retrieval performance of! Back them up with references or personal experience is structured and easy to search visibility... I would ask here is whether I could think the ClickHouse secondary data skipping indexes, which specific.