From ca9786798c3b04b6dfa8723a5ab7fc722272ab6a Mon Sep 17 00:00:00 2001 From: Tyler White <50381805+IndexSeek@users.noreply.github.com> Date: Fri, 12 Apr 2024 07:25:41 -0400 Subject: [PATCH] docs(blog): needle haystack post (#8824) Co-authored-by: Phillip Cloud <417981+cpcloud@users.noreply.github.com> --- docs/posts/varchar-in-a-haystack/index.qmd | 149 ++++++++++++++++++ .../posts/varchar-in-a-haystack/thumbnail.png | Bin 0 -> 835732 bytes 2 files changed, 149 insertions(+) create mode 100644 docs/posts/varchar-in-a-haystack/index.qmd create mode 100644 docs/posts/varchar-in-a-haystack/thumbnail.png diff --git a/docs/posts/varchar-in-a-haystack/index.qmd b/docs/posts/varchar-in-a-haystack/index.qmd new file mode 100644 index 000000000000..3f540c165400 --- /dev/null +++ b/docs/posts/varchar-in-a-haystack/index.qmd @@ -0,0 +1,149 @@ +--- +title: "Varchar in a haystack" +author: "Tyler White" +error: false +date: "2024-03-28" +image: thumbnail.png +categories: + - blog + - data analysis + - puzzle +--- + +## The scenario + +You're a data analyst, and a new ticket landed in your queue. + +> Subject: Urgent: Data Discovery Needed for Critical Analysis +> +> Hi Data Team, +> +> I hope this message finds you well. I'm reaching out with an urgent request +> that directly impacts the company's most critical project. We need to locate +> a specific value within our database but do not know which column it's in. +> Unfortunately, we don't have documentation for this particular table. We are +> looking for the value "NEEDLE" in the table. +> +> We think it is in the X database, Y schema, and Z table. We appreciate your +> help with this urgent matter! + +Whelp, let's give this a try. + +## The table + +To set up this particular problem, we can use pandas to create a table with 5 +columns and 100 rows. We can use the `at` method to update a row with the value +"NEEDLE" to simulate what we need to find. + +```{python} +#| code-fold: true +import pandas as pd +import random +import string +from ibis.interactive import * + + +def random_string(length=10): + return "".join( + random.choice(string.ascii_letters + string.digits) for _ in range(length) + ) + + +data = [[random_string() for _ in range(5)] for _ in range(100)] +column_names = [f"col{i+1}" for i in range(5)] +df = pd.DataFrame(data, columns=column_names) +df.at[42, 'col4'] = "NEEDLE" +t = ibis.memtable(df, name="Z") +``` + +```{python} +t +``` + +## The solution(s) + +There are a few ways we could solve this. + +#### Option 1: write SQL + +We could always spell it out with SQL, including each column that we want to +check in the `WHERE` clause. In this scenario, we know each column is a varchar, +so we can check each one for the value "NEEDLE". + +```sql +SELECT * +FROM Z +WHERE col1 = 'NEEDLE' + OR col2 = 'NEEDLE' + OR col3 = 'NEEDLE' + OR col4 = 'NEEDLE' + OR col5 = 'NEEDLE'; +``` + +This can be time-consuming. You might want something a little more dynamic. + +#### Option 2: write dynamic SQL + +Dynamically constructing the SQL query at runtime can be more complex, but it +offers more flexibility, especially if we have more than five columns. + +```sql +DO $$ +DECLARE + sql text; + where_clause text := ''; +BEGIN + SELECT INTO where_clause + string_agg(quote_ident(column_name) || ' = ''NEEDLE''', ' OR ') + FROM information_schema.columns + WHERE table_name = 'Z' + AND table_schema = 'public' + AND data_type IN ('character varying', 'varchar', 'text', 'char'); + + sql := 'SELECT * + FROM Z + WHERE ' || where_clause; + + EXECUTE sql; +END $$; +``` + +This can be difficult to troubleshoot, and it is easy to get lost in the quote +characters. + +#### Option 3: use Ibis + +We can make use of [`selectors`](../../reference/selectors.qmd)! + +```{python} +expr = t.filter(s.if_any(s.of_type("string"), _ == "NEEDLE")) + +expr +``` + +We can see the **NEEDLE** value hiding in `col4`. + +## The explanation + +`s.of_type("string")` was used to select string columns, then `s.if_any()` +builds up the ORs. The `_ == "NEEDLE"` part is the condition itself, checking +each column for the value. + +Here's the SQL that was generated to help us find it, which is quite similar +to what we would have had to write if we had gone with [Option 1](#option-1-write-sql). + +```{python} +#| echo: false +ibis.to_sql(expr) +``` + +## The conclusion + +Now that we've found the `"NEEDLE"` value, we can provide the information to the +requester. Urgent requests like this require quick and precise responses. + +Our use of Ibis demonstrates how easy it is to simplify navigating large +datasets, and in this case, undocumented ones. + +Please get in touch with us on [GitHub](https://github.com/ibis-project) or +[Zulip](https://ibis-project.zulipchat.com/). 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