diff --git a/docs/en/development/contrib.md b/docs/en/development/contrib.md index 3e76ba9d5c3..aac322f05eb 100644 --- a/docs/en/development/contrib.md +++ b/docs/en/development/contrib.md @@ -18,7 +18,7 @@ SELECT library_name, license_type, license_path FROM system.licenses ORDER BY li Note that the listed libraries are the ones located in the `contrib/` directory of the ClickHouse repository. Depending on the build options, some of the libraries may have not been compiled, and, as a result, their functionality may not be available at runtime. -[Example](https://sql.clickhouse.com/play?query_id=478GCPU7LRTSZJBNY3EJT3) +[Example](https://sql.clickhouse.com?query_id=478GCPU7LRTSZJBNY3EJT3) ## Adding and maintaining third-party libraries diff --git a/docs/en/getting-started/example-datasets/brown-benchmark.md b/docs/en/getting-started/example-datasets/brown-benchmark.md index 30dc900a222..6233a7e80ad 100644 --- a/docs/en/getting-started/example-datasets/brown-benchmark.md +++ b/docs/en/getting-started/example-datasets/brown-benchmark.md @@ -453,4 +453,4 @@ ORDER BY yr, mo; ``` -The data is also available for interactive queries in the [Playground](https://sql.clickhouse.com/play), [example](https://sql.clickhouse.com/play?query_id=1MXMHASDLEQIP4P1D1STND). +The data is also available for interactive queries in the [Playground](https://sql.clickhouse.com), [example](https://sql.clickhouse.com?query_id=1MXMHASDLEQIP4P1D1STND). diff --git a/docs/en/getting-started/example-datasets/cell-towers.md b/docs/en/getting-started/example-datasets/cell-towers.md index fc6e686a7d2..ecfd21e9d2c 100644 --- a/docs/en/getting-started/example-datasets/cell-towers.md +++ b/docs/en/getting-started/example-datasets/cell-towers.md @@ -360,9 +360,9 @@ This screenshot shows cell tower locations with LTE, UMTS, and GSM radios. The ![Dashboard of cell towers by radio type in mcc 204](@site/docs/en/getting-started/example-datasets/images/superset-cell-tower-dashboard.png) :::tip -The data is also available for interactive queries in the [Playground](https://sql.clickhouse.com/play). +The data is also available for interactive queries in the [Playground](https://sql.clickhouse.com). -This [example](https://sql.clickhouse.com/play?query_id=UV8M4MAGS2PWAUOAYAAARM) will populate the username and even the query for you. +This [example](https://sql.clickhouse.com?query_id=UV8M4MAGS2PWAUOAYAAARM) will populate the username and even the query for you. Although you cannot create tables in the Playground, you can run all of the queries and even use Superset (adjust the host name and port number). ::: diff --git a/docs/en/getting-started/example-datasets/github.md b/docs/en/getting-started/example-datasets/github.md index 2146786907b..26a91eee34d 100644 --- a/docs/en/getting-started/example-datasets/github.md +++ b/docs/en/getting-started/example-datasets/github.md @@ -244,13 +244,13 @@ FROM s3('https://datasets-documentation.s3.amazonaws.com/github/commits/clickhou The tool suggests several queries via its help output. We have answered these in addition to some additional supplementary questions of interest. These queries are of approximately increasing complexity vs. the tool's arbitrary order. -This dataset is available in [play.clickhouse.com](https://sql.clickhouse.com/play?query_id=DCQPNPAIMAQXRLHYURLKVJ) in the `git_clickhouse` databases. We provide a link to this environment for all queries, adapting the database name as required. Note that play results may vary from the those presented here due to differences in time of data collection. +This dataset is available in [play.clickhouse.com](https://sql.clickhouse.com?query_id=DCQPNPAIMAQXRLHYURLKVJ) in the `git_clickhouse` databases. We provide a link to this environment for all queries, adapting the database name as required. Note that play results may vary from the those presented here due to differences in time of data collection. ## History of a single file The simplest of queries. Here we look at all commit messages for the `StorageReplicatedMergeTree.cpp`. Since these are likely more interesting, we sort by the most recent messages first. -[play](https://sql.clickhouse.com/play?query_id=COAZRFX2YFULDBXRQTCQ1S) +[play](https://sql.clickhouse.com?query_id=COAZRFX2YFULDBXRQTCQ1S) ```sql SELECT @@ -287,7 +287,7 @@ LIMIT 10 We can also review the line changes, excluding renames i.e. we won't show changes before a rename event when the file existed under a different name: -[play](https://sql.clickhouse.com/play?query_id=AKS9SYLARFMZCHGAAQNEBN) +[play](https://sql.clickhouse.com?query_id=AKS9SYLARFMZCHGAAQNEBN) ```sql SELECT @@ -327,7 +327,7 @@ This is important for later analysis when we only want to consider the current f **Note there appears to have been a broken commit history in relation to files under the `dbms`, `libs`, `tests/testflows/` directories during their renames. We also thus exclude these.** -[play](https://sql.clickhouse.com/play?query_id=2HNFWPCFWEEY92WTAPMA7W) +[play](https://sql.clickhouse.com?query_id=2HNFWPCFWEEY92WTAPMA7W) ```sql SELECT path @@ -369,7 +369,7 @@ LIMIT 10 Note that this allows for files to be renamed and then re-renamed to their original values. First we aggregate `old_path` for a list of deleted files as a result of renaming. We union this with the last operation for every `path`. Finally, we filter this list to those where the final event is not a `Delete`. -[play](https://sql.clickhouse.com/play?query_id=1OXCKMOH2JVMSHD3NS2WW6) +[play](https://sql.clickhouse.com?query_id=1OXCKMOH2JVMSHD3NS2WW6) ```sql SELECT uniq(path) @@ -419,7 +419,7 @@ The difference here is caused by a few factors: - A rename can occur alongside other modifications to the file. These are listed as separate events in file_changes but with the same time. The `argMax` function has no way of distinguishing these - it picks the first value. The natural ordering of the inserts (the only means of knowing the correct order) is not maintained across the union so modified events can be selected. For example, below the `src/Functions/geometryFromColumn.h` file has several modifications before being renamed to `src/Functions/geometryConverters.h`. Our current solution may pick a Modify event as the latest change causing `src/Functions/geometryFromColumn.h` to be retained. -[play](https://sql.clickhouse.com/play?query_id=SCXWMR9GBMJ9UNZYQXQBFA) +[play](https://sql.clickhouse.com?query_id=SCXWMR9GBMJ9UNZYQXQBFA) ```sql SELECT @@ -454,7 +454,7 @@ These differences shouldn't meaningfully impact our analysis. **We welcome impro Limiting to current files, we consider the number of modifications to be the sum of deletes and additions. -[play](https://sql.clickhouse.com/play?query_id=MHXPSBNPTDMJYR3OYSXVR7) +[play](https://sql.clickhouse.com?query_id=MHXPSBNPTDMJYR3OYSXVR7) ```sql WITH current_files AS @@ -507,7 +507,7 @@ LIMIT 10 ## What day of the week do commits usually occur? -[play](https://sql.clickhouse.com/play?query_id=GED2STFSYJDRAA59H8RLIV) +[play](https://sql.clickhouse.com?query_id=GED2STFSYJDRAA59H8RLIV) ```sql SELECT @@ -534,7 +534,7 @@ This makes sense with some productivity drop-off on Fridays. Great to see people This would produce a large query result that is unrealistic to show or visualize if unfiltered. We, therefore, allow a file or subdirectory to be filtered in the following example. Here we group by week using the `toStartOfWeek` function - adapt as required. -[play](https://sql.clickhouse.com/play?query_id=REZRXDVU7CAWT5WKNJSTNY) +[play](https://sql.clickhouse.com?query_id=REZRXDVU7CAWT5WKNJSTNY) ```sql SELECT @@ -578,7 +578,7 @@ This data visualizes well. Below we use Superset. Limit to current files only. -[play](https://sql.clickhouse.com/play?query_id=CYQFNQNK9TAMPU2OZ8KG5Y) +[play](https://sql.clickhouse.com?query_id=CYQFNQNK9TAMPU2OZ8KG5Y) ```sql WITH current_files AS @@ -633,7 +633,7 @@ LIMIT 10 Limited to current files only. -[play](https://sql.clickhouse.com/play?query_id=VWPBPGRZVGTHOCQYWNQZNT) +[play](https://sql.clickhouse.com?query_id=VWPBPGRZVGTHOCQYWNQZNT) ```sql WITH current_files AS @@ -690,7 +690,7 @@ LIMIT 10 Limited to current files only. -[play](https://sql.clickhouse.com/play?query_id=VWPBPGRZVGTHOCQYWNQZNT) +[play](https://sql.clickhouse.com?query_id=VWPBPGRZVGTHOCQYWNQZNT) ```sql WITH current_files AS @@ -750,7 +750,7 @@ Our core data structure, the Merge Tree, is obviously under constant evolution w Do we write more docs at certain times of the month e.g., around release dates? We can use the `countIf` function to compute a simple ratio, visualizing the result using the `bar` function. -[play](https://sql.clickhouse.com/play?query_id=BA4RZUXUHNQBH9YK7F2T9J) +[play](https://sql.clickhouse.com?query_id=BA4RZUXUHNQBH9YK7F2T9J) ```sql SELECT @@ -811,7 +811,7 @@ Maybe a little more near the end of the month, but overall we keep a good even d We consider diversity here to be the number of unique files an author has contributed to. -[play](https://sql.clickhouse.com/play?query_id=MT8WBABUKYBYSBA78W5TML) +[play](https://sql.clickhouse.com?query_id=MT8WBABUKYBYSBA78W5TML) ```sql SELECT @@ -841,7 +841,7 @@ LIMIT 10 Let's see who has the most diverse commits in their recent work. Rather than limit by date, we'll restrict to an author's last N commits (in this case, we've used 3 but feel free to modify): -[play](https://sql.clickhouse.com/play?query_id=4Q3D67FWRIVWTY8EIDDE5U) +[play](https://sql.clickhouse.com?query_id=4Q3D67FWRIVWTY8EIDDE5U) ```sql SELECT @@ -888,7 +888,7 @@ LIMIT 10 Here we select our founder [Alexey Milovidov](https://github.com/alexey-milovidov) and limit our analysis to current files. -[play](https://sql.clickhouse.com/play?query_id=OKGZBACRHVGCRAGCZAJKMF) +[play](https://sql.clickhouse.com?query_id=OKGZBACRHVGCRAGCZAJKMF) ```sql WITH current_files AS @@ -941,7 +941,7 @@ LIMIT 10 This makes sense because Alexey has been responsible for maintaining the Change log. But what if we use the base name of the file to identify his popular files - this allows for renames and should focus on code contributions. -[play](https://sql.clickhouse.com/play?query_id=P9PBDZGOSVTKXEXU73ZNAJ) +[play](https://sql.clickhouse.com?query_id=P9PBDZGOSVTKXEXU73ZNAJ) ```sql SELECT @@ -976,7 +976,7 @@ For this, we first need to identify the largest files. Estimating this via a ful To estimate, assuming we restrict to current files, we sum line additions and subtract deletions. We can then compute a ratio of length to the number of authors. -[play](https://sql.clickhouse.com/play?query_id=PVSDOHZYUMRDDUZFEYJC7J) +[play](https://sql.clickhouse.com?query_id=PVSDOHZYUMRDDUZFEYJC7J) ```sql WITH current_files AS @@ -1031,7 +1031,7 @@ LIMIT 10 Text dictionaries aren't maybe realistic, so lets restrict to code only via a file extension filter! -[play](https://sql.clickhouse.com/play?query_id=BZHGWUIZMPZZUHS5XRBK2M) +[play](https://sql.clickhouse.com?query_id=BZHGWUIZMPZZUHS5XRBK2M) ```sql WITH current_files AS @@ -1085,7 +1085,7 @@ LIMIT 10 There is some recency bias in this - newer files have fewer opportunities for commits. What about if we restrict to files at least 1 yr old? -[play](https://sql.clickhouse.com/play?query_id=RMHHZEDHFUCBGRQVQA2732) +[play](https://sql.clickhouse.com?query_id=RMHHZEDHFUCBGRQVQA2732) ```sql WITH current_files AS @@ -1144,7 +1144,7 @@ LIMIT 10 We interpret this as the number of lines added and removed by the day of the week. In this case, we focus on the [Functions directory](https://github.com/ClickHouse/ClickHouse/tree/master/src/Functions) -[play](https://sql.clickhouse.com/play?query_id=PF3KEMYG5CVLJGCFYQEGB1) +[play](https://sql.clickhouse.com?query_id=PF3KEMYG5CVLJGCFYQEGB1) ```sql SELECT @@ -1171,7 +1171,7 @@ GROUP BY toDayOfWeek(time) AS dayOfWeek And by time of day, -[play](https://sql.clickhouse.com/play?query_id=Q4VDVKEGHHRBCUJHNCVTF1) +[play](https://sql.clickhouse.com?query_id=Q4VDVKEGHHRBCUJHNCVTF1) ```sql SELECT @@ -1215,7 +1215,7 @@ GROUP BY toHour(time) AS hourOfDay This distribution makes sense given most of our development team is in Amsterdam. The `bar` functions helps us visualize these distributions: -[play](https://sql.clickhouse.com/play?query_id=9AZ8CENV8N91YGW7T6IB68) +[play](https://sql.clickhouse.com?query_id=9AZ8CENV8N91YGW7T6IB68) ```sql SELECT @@ -1269,7 +1269,7 @@ FROM The `sign = -1` indicates a code deletion. We exclude punctuation and the insertion of empty lines. -[play](https://sql.clickhouse.com/play?query_id=448O8GWAHY3EM6ZZ7AGLAM) +[play](https://sql.clickhouse.com?query_id=448O8GWAHY3EM6ZZ7AGLAM) ```sql SELECT @@ -1325,7 +1325,7 @@ Alexey clearly likes removing other peoples code. Lets exclude him for a more ba If we consider by just number of commits: -[play](https://sql.clickhouse.com/play?query_id=WXPKFJCAHOKYKEVTWNFVCY) +[play](https://sql.clickhouse.com?query_id=WXPKFJCAHOKYKEVTWNFVCY) ```sql SELECT @@ -1356,7 +1356,7 @@ LIMIT 1 BY day_of_week OK, some possible advantages here to the longest contributor - our founder Alexey. Lets limit our analysis to the last year. -[play](https://sql.clickhouse.com/play?query_id=8YRJGHFTNJAWJ96XCJKKEH) +[play](https://sql.clickhouse.com?query_id=8YRJGHFTNJAWJ96XCJKKEH) ```sql SELECT @@ -1390,7 +1390,7 @@ This is still a little simple and doesn't reflect people's work. A better metric might be who is the top contributor each day as a fraction of the total work performed in the last year. Note that we treat the deletion and adding code equally. -[play](https://sql.clickhouse.com/play?query_id=VQF4KMRDSUEXGS1JFVDJHV) +[play](https://sql.clickhouse.com?query_id=VQF4KMRDSUEXGS1JFVDJHV) ```sql SELECT @@ -1440,7 +1440,7 @@ INNER JOIN We limit the analysis to the current files. For brevity, we restrict the results to a depth of 2 with 5 files per root folder. Adjust as required. -[play](https://sql.clickhouse.com/play?query_id=6YWAUQYPZINZDJGBEZBNWG) +[play](https://sql.clickhouse.com?query_id=6YWAUQYPZINZDJGBEZBNWG) ```sql WITH current_files AS @@ -1523,7 +1523,7 @@ LIMIT 5 BY root For this question, we need the number of lines written by an author divided by the total number of lines they have had removed by another contributor. -[play](https://sql.clickhouse.com/play?query_id=T4DTWTB36WFSEYAZLMGRNF) +[play](https://sql.clickhouse.com?query_id=T4DTWTB36WFSEYAZLMGRNF) ```sql SELECT @@ -1627,7 +1627,7 @@ This doesn't capture the notion of a "re-write" however, where a large portion o The query is limited to the current files only. We list all file changes by grouping by `path` and `commit_hash`, returning the number of lines added and removed. Using a window function, we estimate the file's total size at any moment in time by performing a cumulative sum and estimating the impact of any change on file size as `lines added - lines removed`. Using this statistic, we can calculate the percentage of the file that has been added or removed for each change. Finally, we count the number of file changes that constitute a rewrite per file i.e. `(percent_add >= 0.5) AND (percent_delete >= 0.5) AND current_size > 50`. Note we require files to be more than 50 lines to avoid early contributions to a file being counted as a rewrite. This also avoids a bias to very small files, which may be more likely to be rewritten. -[play](https://sql.clickhouse.com/play?query_id=5PL1QLNSH6QQTR8H9HINNP) +[play](https://sql.clickhouse.com?query_id=5PL1QLNSH6QQTR8H9HINNP) ```sql WITH @@ -1719,7 +1719,7 @@ We query for lines added, joining this with the lines removed - filtering to cas Finally, we aggregate across this dataset to compute the average number of days lines stay in the repository by the day of the week. -[play](https://sql.clickhouse.com/play?query_id=GVF23LEZTNZI22BT8LZBBE) +[play](https://sql.clickhouse.com?query_id=GVF23LEZTNZI22BT8LZBBE) ```sql SELECT @@ -1778,7 +1778,7 @@ GROUP BY dayOfWeek(added_day) AS day_of_week_added This query uses the same principle as [What weekday does the code have the highest chance to stay in the repository](#what-weekday-does-the-code-have-the-highest-chance-to-stay-in-the-repository) - by aiming to uniquely identify a line of code using the path and line contents. This allows us to identify the time between when a line was added and removed. We filter to current files and code only, however, and average the time for each file across lines. -[play](https://sql.clickhouse.com/play?query_id=3CYYT7HEHWRFHVCM9JCKSU) +[play](https://sql.clickhouse.com?query_id=3CYYT7HEHWRFHVCM9JCKSU) ```sql WITH @@ -1869,7 +1869,7 @@ There are a few ways we can address this question. Focusing on the code to test Note we limit to users with more than 20 changes to focus on regular committers and avoid a bias to one-off contributions. -[play](https://sql.clickhouse.com/play?query_id=JGKZSEQDPDTDKZXD3ZCGLE) +[play](https://sql.clickhouse.com?query_id=JGKZSEQDPDTDKZXD3ZCGLE) ```sql SELECT @@ -1911,7 +1911,7 @@ LIMIT 20 We can plot this distribution as a histogram. -[play](https://sql.clickhouse.com/play?query_id=S5AJIIRGSUAY1JXEVHQDAK) +[play](https://sql.clickhouse.com?query_id=S5AJIIRGSUAY1JXEVHQDAK) ```sql WITH ( @@ -1954,7 +1954,7 @@ Most contributors write more code than tests, as you'd expect. What about who adds the most comments when contributing code? -[play](https://sql.clickhouse.com/play?query_id=EXPHDIURBTOXXOK1TGNNYD) +[play](https://sql.clickhouse.com?query_id=EXPHDIURBTOXXOK1TGNNYD) ```sql SELECT @@ -2038,7 +2038,7 @@ To compute this, we first work out each author's comments ratio over time - simi After calculating the average by-week offset across all authors, we sample these results by selecting every 10th week. -[play](https://sql.clickhouse.com/play?query_id=SBHEWR8XC4PRHY13HPPKCN) +[play](https://sql.clickhouse.com?query_id=SBHEWR8XC4PRHY13HPPKCN) ```sql WITH author_ratios_by_offset AS @@ -2116,7 +2116,7 @@ Encouragingly, our comment % is pretty constant and doesn't degrade the longer a We can use the same principle as [List files that were rewritten most number of time or by most of authors](#list-files-that-were-rewritten-most-number-of-time-or-by-most-of-authors) to identify rewrites but consider all files. A window function is used to compute the time between rewrites for each file. From this, we can calculate an average and median across all files. -[play](https://sql.clickhouse.com/play?query_id=WSHUEPJP9TNJUH7QITWWOR) +[play](https://sql.clickhouse.com?query_id=WSHUEPJP9TNJUH7QITWWOR) ```sql WITH @@ -2176,7 +2176,7 @@ FROM rewrites Similar to [What is the average time before code will be rewritten and the median (half-life of code decay)?](#what-is-the-average-time-before-code-will-be-rewritten-and-the-median-half-life-of-code-decay) and [List files that were rewritten most number of time or by most of authors](#list-files-that-were-rewritten-most-number-of-time-or-by-most-of-authors), except we aggregate by day of week. Adjust as required e.g. month of year. -[play](https://sql.clickhouse.com/play?query_id=8PQNWEWHAJTGN6FTX59KH2) +[play](https://sql.clickhouse.com?query_id=8PQNWEWHAJTGN6FTX59KH2) ```sql WITH @@ -2240,7 +2240,7 @@ GROUP BY dayOfWeek We define "sticky" as how long does an author's code stay before its rewritten. Similar to the previous question [What is the average time before code will be rewritten and the median (half-life of code decay)?](#what-is-the-average-time-before-code-will-be-rewritten-and-the-median-half-life-of-code-decay) - using the same metric for rewrites i.e. 50% additions and 50% deletions to the file. We compute the average rewrite time per author and only consider contributors with more than two files. -[play](https://sql.clickhouse.com/play?query_id=BKHLVVWN5SET1VTIFQ8JVK) +[play](https://sql.clickhouse.com?query_id=BKHLVVWN5SET1VTIFQ8JVK) ```sql WITH @@ -2319,7 +2319,7 @@ This query first requires us to calculate the days when an author has committed. Our subsequent array functions compute each author's longest sequence of consecutive ones. First, the `groupArray` function is used to collate all `consecutive_day` values for an author. This array of 1s and 0s, is then split on 0 values into subarrays. Finally, we calculate the longest subarray. -[play](https://sql.clickhouse.com/play?query_id=S3E64UYCAMDAYJRSXINVFR) +[play](https://sql.clickhouse.com?query_id=S3E64UYCAMDAYJRSXINVFR) ```sql WITH commit_days AS @@ -2372,7 +2372,7 @@ LIMIT 10 Files can be renamed. When this occurs, we get a rename event, where the `path` column is set to the new path of the file and the `old_path` represents the previous location e.g. -[play](https://sql.clickhouse.com/play?query_id=AKTW3Z8JZAPQ4H9BH2ZFRX) +[play](https://sql.clickhouse.com?query_id=AKTW3Z8JZAPQ4H9BH2ZFRX) ```sql SELECT diff --git a/docs/en/getting-started/example-datasets/menus.md b/docs/en/getting-started/example-datasets/menus.md index 85eaa9661ef..a364085eeeb 100644 --- a/docs/en/getting-started/example-datasets/menus.md +++ b/docs/en/getting-started/example-datasets/menus.md @@ -354,4 +354,4 @@ At least they have caviar with vodka. Very nice. ## Online Playground {#playground} -The data is uploaded to ClickHouse Playground, [example](https://sql.clickhouse.com/play?query_id=KB5KQJJFNBKHE5GBUJCP1B). +The data is uploaded to ClickHouse Playground, [example](https://sql.clickhouse.com?query_id=KB5KQJJFNBKHE5GBUJCP1B). diff --git a/docs/en/getting-started/example-datasets/ontime.md b/docs/en/getting-started/example-datasets/ontime.md index 5685f5ba22b..5e1f7c9c97f 100644 --- a/docs/en/getting-started/example-datasets/ontime.md +++ b/docs/en/getting-started/example-datasets/ontime.md @@ -386,7 +386,7 @@ ORDER BY c DESC LIMIT 10; ``` -You can also play with the data in Playground, [example](https://sql.clickhouse.com/play?query_id=M4FSVBVMSHY98NKCQP8N4K). +You can also play with the data in Playground, [example](https://sql.clickhouse.com?query_id=M4FSVBVMSHY98NKCQP8N4K). This performance test was created by Vadim Tkachenko. See: diff --git a/docs/en/getting-started/example-datasets/opensky.md b/docs/en/getting-started/example-datasets/opensky.md index c9e1e52bd01..22f88ce274a 100644 --- a/docs/en/getting-started/example-datasets/opensky.md +++ b/docs/en/getting-started/example-datasets/opensky.md @@ -417,4 +417,4 @@ Result: ### Online Playground {#playground} -You can test other queries to this data set using the interactive resource [Online Playground](https://sql.clickhouse.com/play). For example, [like this](https://sql.clickhouse.com/play?query_id=BIPDVQNIGVEZFQYFEFQB7O). However, please note that you cannot create temporary tables here. +You can test other queries to this data set using the interactive resource [Online Playground](https://sql.clickhouse.com). For example, [like this](https://sql.clickhouse.com?query_id=BIPDVQNIGVEZFQYFEFQB7O). However, please note that you cannot create temporary tables here. diff --git a/docs/en/getting-started/example-datasets/recipes.md b/docs/en/getting-started/example-datasets/recipes.md index af1adfb85b7..78520a34248 100644 --- a/docs/en/getting-started/example-datasets/recipes.md +++ b/docs/en/getting-started/example-datasets/recipes.md @@ -335,4 +335,4 @@ Result: ### Online Playground -The dataset is also available in the [Online Playground](https://sql.clickhouse.com/play?query_id=HQXNQZE26Z1QWYP9KC76ML). +The dataset is also available in the [Online Playground](https://sql.clickhouse.com?query_id=HQXNQZE26Z1QWYP9KC76ML). diff --git a/docs/en/getting-started/example-datasets/uk-price-paid.md b/docs/en/getting-started/example-datasets/uk-price-paid.md index 2d638428a0f..edc9b0956a9 100644 --- a/docs/en/getting-started/example-datasets/uk-price-paid.md +++ b/docs/en/getting-started/example-datasets/uk-price-paid.md @@ -447,4 +447,4 @@ With projection: 100 rows in set. Elapsed: 0.336 sec. Processed 17.32 thousand r ### Test it in the Playground {#playground} -The dataset is also available in the [Online Playground](https://sql.clickhouse.com/play?query_id=TRCWH5ZETY4SEEK8ISCCAX). +The dataset is also available in the [Online Playground](https://sql.clickhouse.com?query_id=TRCWH5ZETY4SEEK8ISCCAX). diff --git a/docs/en/getting-started/playground.md b/docs/en/getting-started/playground.md index 63faabf2be2..80b6f9a9889 100644 --- a/docs/en/getting-started/playground.md +++ b/docs/en/getting-started/playground.md @@ -8,7 +8,7 @@ slug: /en/getting-started/playground # ClickHouse Playground -[ClickHouse Playground](https://sql.clickhouse.com/play) allows people to experiment with ClickHouse by running queries instantly, without setting up their server or cluster. +[ClickHouse Playground](https://sql.clickhouse.com) allows people to experiment with ClickHouse by running queries instantly, without setting up their server or cluster. Several example datasets are available in Playground. You can make queries to Playground using any HTTP client, for example [curl](https://curl.haxx.se) or [wget](https://www.gnu.org/software/wget/), or set up a connection using [JDBC](../interfaces/jdbc.md) or [ODBC](../interfaces/odbc.md) drivers. More information about software products that support ClickHouse is available [here](../integrations/index.mdx). diff --git a/docs/ru/development/contrib.md b/docs/ru/development/contrib.md index 700bb48e8fc..67da2b2a6bf 100644 --- a/docs/ru/development/contrib.md +++ b/docs/ru/development/contrib.md @@ -93,7 +93,7 @@ sidebar_label: "Используемые сторонние библиотеки SELECT library_name, license_type, license_path FROM system.licenses ORDER BY library_name COLLATE 'en'; ``` -[Пример](https://sql.clickhouse.com/play?query_id=478GCPU7LRTSZJBNY3EJT3) +[Пример](https://sql.clickhouse.com?query_id=478GCPU7LRTSZJBNY3EJT3) ## Рекомендации по добавлению сторонних библиотек и поддержанию в них пользовательских изменений {#adding-third-party-libraries} diff --git a/docs/ru/getting-started/example-datasets/brown-benchmark.md b/docs/ru/getting-started/example-datasets/brown-benchmark.md index cd491666d40..d37be9f48d5 100644 --- a/docs/ru/getting-started/example-datasets/brown-benchmark.md +++ b/docs/ru/getting-started/example-datasets/brown-benchmark.md @@ -412,4 +412,4 @@ ORDER BY yr, mo; ``` -Данные также доступны для работы с интерактивными запросами через [Playground](https://sql.clickhouse.com/play), [пример](https://sql.clickhouse.com/play?query_id=1MXMHASDLEQIP4P1D1STND). +Данные также доступны для работы с интерактивными запросами через [Playground](https://sql.clickhouse.com), [пример](https://sql.clickhouse.com?query_id=1MXMHASDLEQIP4P1D1STND). diff --git a/docs/ru/getting-started/example-datasets/cell-towers.md b/docs/ru/getting-started/example-datasets/cell-towers.md index a3341836390..2f91bed1c04 100644 --- a/docs/ru/getting-started/example-datasets/cell-towers.md +++ b/docs/ru/getting-started/example-datasets/cell-towers.md @@ -126,4 +126,4 @@ SELECT count() FROM cell_towers WHERE pointInPolygon((lon, lat), (SELECT * FROM 1 rows in set. Elapsed: 0.067 sec. Processed 43.28 million rows, 692.42 MB (645.83 million rows/s., 10.33 GB/s.) ``` -Вы можете протестировать другие запросы с помощью интерактивного ресурса [Playground](https://sql.clickhouse.com/play). Например, [вот так](https://sql.clickhouse.com/play?query_id=UV8M4MAGS2PWAUOAYAAARM). Однако, обратите внимание, что здесь нельзя создавать временные таблицы. +Вы можете протестировать другие запросы с помощью интерактивного ресурса [Playground](https://sql.clickhouse.com). Например, [вот так](https://sql.clickhouse.com?query_id=UV8M4MAGS2PWAUOAYAAARM). Однако, обратите внимание, что здесь нельзя создавать временные таблицы. diff --git a/docs/ru/getting-started/example-datasets/recipes.md b/docs/ru/getting-started/example-datasets/recipes.md index 55a57ed3d65..860d1ff450c 100644 --- a/docs/ru/getting-started/example-datasets/recipes.md +++ b/docs/ru/getting-started/example-datasets/recipes.md @@ -338,4 +338,4 @@ WHERE title = 'Chocolate-Strawberry-Orange Wedding Cake'; ### Online Playground -Этот набор данных доступен в [Online Playground](https://sql.clickhouse.com/play?query_id=HQXNQZE26Z1QWYP9KC76ML). +Этот набор данных доступен в [Online Playground](https://sql.clickhouse.com?query_id=HQXNQZE26Z1QWYP9KC76ML). diff --git a/docs/ru/getting-started/playground.md b/docs/ru/getting-started/playground.md index 827f07ef92c..b4ec89784ac 100644 --- a/docs/ru/getting-started/playground.md +++ b/docs/ru/getting-started/playground.md @@ -6,7 +6,7 @@ sidebar_label: Playground # ClickHouse Playground {#clickhouse-playground} -[ClickHouse Playground](https://sql.clickhouse.com/play) позволяет пользователям экспериментировать с ClickHouse, выполняя запросы мгновенно, без необходимости настройки сервера или кластера. +[ClickHouse Playground](https://sql.clickhouse.com) позволяет пользователям экспериментировать с ClickHouse, выполняя запросы мгновенно, без необходимости настройки сервера или кластера. В Playground доступны несколько примеров наборов данных. Вы можете выполнять запросы к Playground, используя любой HTTP-клиент, например [curl](https://curl.haxx.se) или [wget](https://www.gnu.org/software/wget/), или настроить соединение, используя драйверы [JDBC](../interfaces/jdbc.md) или [ODBC](../interfaces/odbc.md). Дополнительную информацию о программных продуктах, поддерживающих ClickHouse, можно найти [здесь](../interfaces/index.md). diff --git a/docs/zh/getting-started/example-datasets/brown-benchmark.mdx b/docs/zh/getting-started/example-datasets/brown-benchmark.mdx index 86364678bea..74bfeb58d6d 100644 --- a/docs/zh/getting-started/example-datasets/brown-benchmark.mdx +++ b/docs/zh/getting-started/example-datasets/brown-benchmark.mdx @@ -457,4 +457,4 @@ ORDER BY yr, mo; ``` -此数据集可在 [Playground](https://sql.clickhouse.com/play) 中进行交互式的请求, [example](https://sql.clickhouse.com/play?query_id=1MXMHASDLEQIP4P1D1STND). +此数据集可在 [Playground](https://sql.clickhouse.com) 中进行交互式的请求, [example](https://sql.clickhouse.com?query_id=1MXMHASDLEQIP4P1D1STND). diff --git a/docs/zh/getting-started/example-datasets/cell-towers.mdx b/docs/zh/getting-started/example-datasets/cell-towers.mdx index a225dca3632..b98e92c378a 100644 --- a/docs/zh/getting-started/example-datasets/cell-towers.mdx +++ b/docs/zh/getting-started/example-datasets/cell-towers.mdx @@ -228,5 +228,5 @@ WHERE pointInPolygon((lon, lat), (SELECT * FROM moscow)) 1 rows in set. Elapsed: 0.067 sec. Processed 43.28 million rows, 692.42 MB (645.83 million rows/s., 10.33 GB/s.) ``` -虽然不能创建临时表，但此数据集仍可在 [Playground](https://sql.clickhouse.com/play) 中进行交互式的请求, [example](https://sql.clickhouse.com/play?query_id=UV8M4MAGS2PWAUOAYAAARM). +虽然不能创建临时表，但此数据集仍可在 [Playground](https://sql.clickhouse.com) 中进行交互式的请求, [example](https://sql.clickhouse.com?query_id=UV8M4MAGS2PWAUOAYAAARM). diff --git a/docs/zh/getting-started/example-datasets/menus.mdx b/docs/zh/getting-started/example-datasets/menus.mdx index acc4093c951..33ec031c1ad 100644 --- a/docs/zh/getting-started/example-datasets/menus.mdx +++ b/docs/zh/getting-started/example-datasets/menus.mdx @@ -349,4 +349,4 @@ ORDER BY d ASC; ## 在线 Playground{#playground} -此数据集已经上传到了 ClickHouse Playground 中，[example](https://sql.clickhouse.com/play?query_id=KB5KQJJFNBKHE5GBUJCP1B)。 +此数据集已经上传到了 ClickHouse Playground 中，[example](https://sql.clickhouse.com?query_id=KB5KQJJFNBKHE5GBUJCP1B)。 diff --git a/docs/zh/getting-started/example-datasets/opensky.mdx b/docs/zh/getting-started/example-datasets/opensky.mdx index 26fb31f75aa..0116515b28f 100644 --- a/docs/zh/getting-started/example-datasets/opensky.mdx +++ b/docs/zh/getting-started/example-datasets/opensky.mdx @@ -413,4 +413,4 @@ ORDER BY k ASC; ### 在线 Playground {#playground} -你可以使用交互式资源 [Online Playground](https://sql.clickhouse.com/play) 来尝试对此数据集的其他查询。 例如, [执行这个查询](https://sql.clickhouse.com/play?query_id=BIPDVQNIGVEZFQYFEFQB7O). 但是，请注意无法在 Playground 中创建临时表。 +你可以使用交互式资源 [Online Playground](https://sql.clickhouse.com) 来尝试对此数据集的其他查询。 例如, [执行这个查询](https://sql.clickhouse.com?query_id=BIPDVQNIGVEZFQYFEFQB7O). 但是，请注意无法在 Playground 中创建临时表。 diff --git a/docs/zh/getting-started/example-datasets/recipes.mdx b/docs/zh/getting-started/example-datasets/recipes.mdx index 4dd674d6562..a7b3ddbe0da 100644 --- a/docs/zh/getting-started/example-datasets/recipes.mdx +++ b/docs/zh/getting-started/example-datasets/recipes.mdx @@ -334,6 +334,6 @@ WHERE title = 'Chocolate-Strawberry-Orange Wedding Cake' ### 在线 Playground -此数据集也可在 [在线 Playground](https://sql.clickhouse.com/play?query_id=HQXNQZE26Z1QWYP9KC76ML) 中体验。 +此数据集也可在 [在线 Playground](https://sql.clickhouse.com?query_id=HQXNQZE26Z1QWYP9KC76ML) 中体验。 [原文链接](https://clickhouse.com/docs/en/getting-started/example-datasets/recipes/) diff --git a/docs/zh/getting-started/example-datasets/uk-price-paid.mdx b/docs/zh/getting-started/example-datasets/uk-price-paid.mdx index bdb5528d8a3..158ce08216c 100644 --- a/docs/zh/getting-started/example-datasets/uk-price-paid.mdx +++ b/docs/zh/getting-started/example-datasets/uk-price-paid.mdx @@ -447,4 +447,4 @@ With projection: 100 rows in set. Elapsed: 0.336 sec. Processed 17.32 thousand r ### 在 Playground 上测试{#playground} -也可以在 [Online Playground](https://sql.clickhouse.com/play?query_id=TRCWH5ZETY4SEEK8ISCCAX) 上找到此数据集。 +也可以在 [Online Playground](https://sql.clickhouse.com?query_id=TRCWH5ZETY4SEEK8ISCCAX) 上找到此数据集。 diff --git a/docs/zh/getting-started/playground.md b/docs/zh/getting-started/playground.md index ee9b6b5e04c..5d8927d8a6c 100644 --- a/docs/zh/getting-started/playground.md +++ b/docs/zh/getting-started/playground.md @@ -6,7 +6,7 @@ sidebar_label: 体验平台 # ClickHouse Playground {#clickhouse-playground} -无需搭建服务或集群，[ClickHouse Playground](https://sql.clickhouse.com/play)允许人们通过执行查询语句立即体验ClickHouse，在Playground中我们提供了一些示例数据集。 +无需搭建服务或集群，[ClickHouse Playground](https://sql.clickhouse.com)允许人们通过执行查询语句立即体验ClickHouse，在Playground中我们提供了一些示例数据集。 你可以使用任意HTTP客户端向Playground提交查询语句，比如[curl](https://curl.haxx.se)或者[wget](https://www.gnu.org/software/wget/)，也可以通过[JDBC](../interfaces/jdbc.md)或者[ODBC](../interfaces/odbc.md)驱动建立连接，更多信息详见[客户端](../interfaces/index.md)。