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The join() method of Array instances creates and returns a new string by concatenating all of the elements in this array, separated by commas or a specified separator string. If the array has only one item, then that item will be returned without using the separator.

Array.prototype.join recursively converts each element, including other arrays, to strings. Because the string returned by Array.prototype.toString (which is the same as calling join()) does not have delimiters, nested arrays look like they are flattened. You can only control the separator of the first level, while deeper levels always use the default comma.

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\n The join() method of Array instances creates and\n returns a new string by concatenating all of the elements in this array,\n separated by commas or a specified separator string. If the array has\n only one item, then that item will be returned without using the separator.\n

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INNER JOIN and , (comma) are semantically equivalent in the absence of a join condition: both produce a Cartesian product between the specified tables (that is, each and every row in the first table is joined to each and every row in the second table).

However, the precedence of the comma operator is less than that of INNER JOIN, CROSS JOIN, LEFT JOIN, and so on. If you mix comma joins with the other join types when there is a join condition, an error of the form Unknown column 'col_name' in 'on clause' may occur. Information about dealing with this problem is given later in this section.

The search_condition used with ON is any conditional expression of the form that can be used in a WHERE clause. Generally, the ON clause serves for conditions that specify how to join tables, and the WHERE clause restricts which rows to include in the result set.

The USING(join_column_list) clause names a list of columns that must exist in both tables. If tables a and b both contain columns c1, c2, and c3, the following join compares corresponding columns from the two tables:

The { OJ ... } syntax shown in the join syntax description exists only for compatibility with ODBC. The curly braces in the syntax should be written literally; they are not metasyntax as used elsewhere in syntax descriptions.

STRAIGHT_JOIN is similar to JOIN, except that the left table is always read before the right table. This can be used for those (few) cases for which the join optimizer processes the tables in a suboptimal order.

In the first SELECT statement, column j appears in both tables and thus becomes a join column, so, according to standard SQL, it should appear only once in the output, not twice. Similarly, in the second SELECT statement, column j is named in the USING clause and should appear only once in the output, not twice.

The single result column that replaces two common columns is defined using the coalesce operation. That is, for two t1.a and t2.a the resulting single join column a is defined as a = COALESCE(t1.a, t2.a), where:

A consequence of the definition of coalesced columns is that, for outer joins, the coalesced column contains the value of the non-NULL column if one of the two columns is always NULL. If neither or both columns are NULL, both common columns have the same value, so it doesn't matter which one is chosen as the value of the coalesced column. A simple way to interpret this is to consider that a coalesced column of an outer join is represented by the common column of the inner table of a JOIN. Suppose that the tables t1(a, b) and t2(a, c) have the following contents:

With respect to determining which columns to display for SELECT * expansion, the two joins are not semantically identical. The USING join selects the coalesced value of corresponding columns, whereas the ON join selects all columns from all tables. For the USING join, SELECT * selects these values:

With an inner join, COALESCE(a.c1, b.c1) is the same as either a.c1 or b.c1 because both columns have the same value. With an outer join (such as LEFT JOIN), one of the two columns can be NULL. That column is omitted from the result.

The statement fails with an Unknown column 'i3' in 'on clause' error because i3 is a column in t3, which is not an operand of the ON clause. To enable the join to be processed, rewrite the statement as follows:

JOIN has higher precedence than the comma operator (,), so the join expression t1, t2 JOIN t3 is interpreted as (t1, (t2 JOIN t3)), not as ((t1, t2) JOIN t3). This affects statements that use an ON clause because that clause can refer only to columns in the operands of the join, and the precedence affects interpretation of what those operands are.

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(1) grandmothers, mothers, sisters, spouses, and direct and adopted female descendants of members of The American Legion; and

(2) grandmothers, mothers, sisters, spouses, and direct and adopted female descendants of all men and women who served in either of the following periods: April 6, 1917, to November 11, 1918 and any time after December 7, 1941 who, being a citizen of the United States at the time of their entry therein served on active duty in the Armed Forces of any of the governments associated with the United States during either eligibility periods and died in the line of duty or after honorable discharge;

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if concatenating bytes objects, you can similarly usebytes.join() or io.BytesIO, or you can do in-placeconcatenation with a bytearray object. bytearrayobjects are mutable and have an efficient overallocation mechanism

The subset and equality comparisons do not generalize to a total orderingfunction. For example, any two nonempty disjoint sets are not equal and are notsubsets of each other, so all of the following return False: ab.

A join clause in the Structured Query Language (SQL) combines columns from one or more tables into a new table. The operation corresponds to a join operation in relational algebra. Informally, a join stitches two tables and puts on the same row records with matching fields : INNER, LEFT OUTER, RIGHT OUTER, FULL OUTER and CROSS.

CROSS JOIN does not itself apply any predicate to filter rows from the joined table. The results of a CROSS JOIN can be filtered using a WHERE clause, which may then produce the equivalent of an inner join.

An inner join (or join) requires each row in the two joined tables to have matching column values, and is a commonly used join operation in applications but should not be assumed to be the best choice in all situations. Inner join creates a new result table by combining column values of two tables (A and B) based upon the join-predicate. The query compares each row of A with each row of B to find all pairs of rows that satisfy the join-predicate. When the join-predicate is satisfied by matching non-NULL values, column values for each matched pair of rows of A and B are combined into a result row. ff782bc1db