第一个列向量是正2，负1，对么？
所以这是第一个列向量，向量1。
倍的x，当我用一个向量乘以一个矩阵时，我得到了一个列向量的(线性)组合。
A times x, when I multiply a matrix by a vector, I get a combination of the column.
只要记住：如果你要用一个方阵，乘以一个列向量，当矩阵在左，向量在右的时候乘积才有意义。
It's just something to remember: if you have a square matrix times a column vector, the product that makes sense is with the matrix on the left, and the vector on the right.
假设我将它改成…如果我将前两列相加，我会得到一个向量 [1， 1，-3]。
Let me change it to suppose… if I add those first two columns, that would give me a [1, 1, -3].
Time维度表中满足过滤条件的 time_id连接键被散列以创建一个位向量，用于过滤以上跳跃式扫描的Orders 表行。
The time_id join keys that meet the filter requirements on the Time dimension table are hashed to create a bit vector that filters rows of the Orders table from the skip scan above.
一个直接的分析可以采用聚类分析(可能很大)的列向量。
A straight forward analysis would be to use clustering on the (possible very large) column vectors.
竞赛矩阵和竞赛图由于具有固定行和向量及列和向量的非负矩阵类的计数，是组合数学的一个非常困难的问题，因此对具有固定得分向量的竞赛矩阵的计数问题也比较困难。
But it is very difficult to compute the number of non-negative matrix with fixed score row or column vectors, so to compute the number of tournament matrix with fixed score vector is also difficult.
竞赛矩阵和竞赛图由于具有固定行和向量及列和向量的非负矩阵类的计数，是组合数学的一个非常困难的问题，因此对具有固定得分向量的竞赛矩阵的计数问题也比较困难。
But it is very difficult to compute the number of non-negative matrix with fixed score row or column vectors, so to compute the number of tournament matrix with fixed score vector is also difficult.
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